{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.2. Data Visualization Via Matplotlib"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2.1. Line Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "%matplotlib inline  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x15a6cb85ec8>]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import numpy as np  \n",
    "import math  \n",
    "  \n",
    "x_vals = np.linspace(0, 20, 20)  \n",
    "y_vals = [math.sqrt(i) for i in x_vals]  \n",
    "plt.plot(x_vals, y_vals)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x15a7005c488>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import numpy as np  \n",
    "import math  \n",
    "  \n",
    "x_vals = np.linspace(0, 20, 20)  \n",
    "y_vals = [math.sqrt(i) for i in x_vals]  \n",
    "  \n",
    "fig = plt.figure()  \n",
    "ax = plt.axes()  \n",
    "ax.plot(x_vals, y_vals)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x15a700f1e88>]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import numpy as np  \n",
    "import math  \n",
    " \n",
    "plt.rcParams[\"figure.figsize\"] = [8,6]  \n",
    " \n",
    "x_vals = np.linspace(0, 20, 20)  \n",
    "y_vals = [math.sqrt(i) for i in x_vals]  \n",
    "plt.plot(x_vals, y_vals)  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2.2. Titles - Labels and Legends"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x15a7003bc08>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import numpy as np  \n",
    "import math  \n",
    " \n",
    "x_vals = np.linspace(0, 20, 20)  \n",
    "y_vals = [math.sqrt(i) for i in x_vals]  \n",
    "plt.xlabel('X Values')  \n",
    "plt.ylabel('Y Values')  \n",
    "plt.title('Square Roots')  \n",
    "plt.plot(x_vals, y_vals)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x15a7019dac8>]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAegAAAGDCAYAAADgY4OVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nO3dd7hU1bnH8e8roqLYJSpRghpL7AW99pLYG2oUNbHEJGISNcZgjCa53jRjbzGxYEOxopEjYsXeCyrGirEFW0RRRMRCWfePNSQnx9OAM7OnfD/Pcx6m7Jl5N3NmfmetvfZakVJCkiRVl7mKLkCSJH2ZAS1JUhUyoCVJqkIGtCRJVciAliSpChnQkiRVIQNakqQqZEBLFRIRm0bEQxHxUUR8EBEPRsT6RdfVkYj4XkRMj4jJETEpIp6OiJ276LmHRMQfu+K5pHpjQEsVEBELASOBs4HFgK8CvwM+L6CWbrPxsIdTSj2BRYBzgKsjYpGurUxScwa0VBkrAaSUrkopTU8pfZpSuj2l9HfIoRkRp0bE+xHxakQcGhEpIuYu3f96RGw988ki4rcRcXmz69dGxL9KrfP7ImK1ZvcNiYhzI+LmiPgE2Coi5i293riIeDcizouIHh3tREppBjAUWABYsdlr7BoRz0XExIi4JyK+0ey+b5Rum1jaZtfS7QOB7wJHl1rnN5Zu/2VEvBURH0fE2Ij41uz9l0u1zYCWKuMlYHpEXBoRO0TEoi3uPxjYGVgH6AfsOYvPfws5ML8CPAlc0eL+7wDHAwsCDwAnkf9oWBv4OrlFf1xHL1JqfR8ETAX+WbptJeAq4GdAL+Bm4MaImCciugM3AreXajscuCIiVk4pDS7VeXJKqWdKaZeIWBk4DFg/pbQgsB3w+iz+X0h1wYCWKiClNAnYFEjABcB7ETEiIpYsbTIAODOl9EZK6QPghFl8/otTSh+nlD4HfgusFRELN9vkhpTSg6UW8OfkPwiOTCl9kFL6GPgTsE87L7FhREwEPgNOBfZLKY0v3bc3cFNKaVRKaWrp/h7AxsCGQE/gxJTSFymlu8hd/fu28TrTgXmBVSOie0rp9ZTSK7PyfyHVCwNaqpCU0gsppe+llJYBVgd6A2eW7u4NvNFs83929nlL3eMnRsQrETGJ/7Q4l2i2WfPn7gXMDzxR6naeCNxaur0tj6SUFgEWBUYAmzW7r3fzekt/BLxBbpX3Bt4o3dZ8377a2ouklF4mt8R/C4yPiKsjonc7dUl1y4CWCpBSehEYQg5qgHeAZZtt0qfFQz4hh+pMSzW7/B2gP7A1sDDQt3R7NH/JZpffBz4FVkspLVL6Wbg0CKyjuicDPwH2j4h1Sje/DXxt5jYREaV9eat037IR0fy7pk/pvpZ1zXyNK1NKm5aeM5G746WGY0BLFRARq0TEoIhYpnR9WXI37yOlTYYBP42IZUrHp49p8RRjgH0iontEtDxGvSC523oCOcT/1F4tpdbsBcAZEfGVUj1fjYjtOrMvKaUJwIX855j1MGCniPhW6ZjzoFI9DwGPkv+4OLpU+5bALsDVpce+Cyw/87kjYuWI+GZEzEvuTv+U3O0tNRwDWqqMj4H/AR4tjaR+BHiWHGaQA/M24GnyIK/rWzz+f4EVgA/Jp2dd2ey+y8jdxm8Bz/Of0G/PL4GXgUdK3eJ3ACvPwv6cCewYEWumlMYC+5FPIXufHMC7lI45fwHsCuxQuu8c4IBSDwLAReTjzRMjool8/PnE0rb/Ig8s+9Us1CXVjUjpSz1MkgoWEX2B14DuKaVpxVYjqQi2oCVJqkIGtCRJVcgubkmSqpAtaEmSqpABLUlSFZq76AKaW2KJJVLfvn2LLkOSpIp44okn3k8ptTqLX1UFdN++fRk9enTRZUiSVBER0ea0vnZxS5JUhQxoSZKqkAEtSVIVMqAlSapCBrQkSVXIgJYkqQoZ0JIkVSEDWpKkKmRAS5JUhQxoSZKqkAEtSVIVMqAlSerI9OkwahS8+WbFXtKAliSpLS+8AMccA1/7Gmy7LVxyScVeuqpWs5IkqXATJsDVV8Oll8Ljj0O3brD99nD66bDrrhUrw4CWJOmLL+CWW3IojxwJU6fCmmvCaafBd74DSy1V8ZIMaElSY0oJnnwSLrsMrrwS3n8fvvIVOOwwOPBAWGutQsszoCVJjeXtt+GKK3Jr+bnnYJ55oH//HMrbbgvduxddIWBAS5IawaefQlNTDuVRo2DGDNhwQzj3XNh7b1h00aIr/BIDWpJUn1KCBx/MoTxsGEyaBH36wLHHwgEHwEorFV1huwxoSVJ9ef31fFz5ssvglVdggQVgzz1zF/YWW8BctXGGsQEtSap9U6bA8OFw8cVw110QAVttBccdB3vsAT17Fl3hLDOgJUm1KSV47LE8echVV+Uu7OWXh9//PreW+/QpusI5YkBLkmrLu+/C0KE5mJ9/Hnr0gL32goMOgs03r5ku7I4Y0JKk6jd1Ktx0Uw7lm27Kc2NvtBFccAEMGAALLVR0hV3OgJYkVa9nn82hfPnlMH58ntFr0KDcWl5llaKrKysDWpJUXSZOzMeUL7kkz4XdvTvssksO5e23h7kbI7oaYy8lSdVtxow8+vrii/No7M8+gzXWgDPOgO9+F3r1KrrCijOgJUnFee01GDIk/4wbB4ssAj/4QW4tr7tuPl2qQRnQkqTK+vzzPO3mhRfCHXfkEN5mGzj55Dwn9nzzFV1hVTCgJUmV8fzzOZQvuyyvudynD/zud7m1vOyyRVdXdQxoSVL5fPJJngf7wgvhoYfygK/+/eHgg+Fb34Ju3YqusGoZ0JKkrjVzneULLsjrLH/8May8Mpx6Kuy/f15zWR0yoCVJXWPixLzO8oUXwpgxeYavAQPghz+ETTZp6AFfs8OAliTNvpTggQdya/naa/PpUeusA+ecA/vum0dla7YY0JKkWTd+fF5n+cIL4aWX8lSbBx2UW8vrrlt0dXXBgJYkdc706TBqVA7lG26AadNg003hV7/K6y0vsEDRFdYVA1qS1L533oGLLsrd2OPGwRJLwBFH5AlFvvGNoqurWwa0JOnLZsyAO++E887LreXp02HrrfNI7P79YZ55iq6w7hnQkqT/GD8+T7t5/vnw6qu5tfzzn8PAgfD1rxddXUMxoCWp0aUE996bQ/lvf8trL2++Ofzxj7DHHjDvvEVX2JDKHtAR0Q0YDbyVUtq53K8nSeqkDz7II7HPPx/Gjs2nRP3kJ3DIIR5brgKVaEEfAbwALFSB15IktSclePjhfGx52LC8cMWGG+Zu7QED8uQiqgplDeiIWAbYCTge+Hk5X0uS1I6PPoLLL8/B/OyzsOCC8P3v59byWmsVXZ1aUe4W9JnA0cCCZX4dSVJrRo/OoXzVVTBlSp5EZPDgPMtXz55FV6d2lC2gI2JnYHxK6YmI2LKd7QYCAwH69OlTrnIkqXFMnpwD+bzz8qIV88+fA/lHP4J+/YquTp1Uzhb0JsCuEbEjMB+wUERcnlLar/lGKaXBwGCAfv36pTLWI0n1bezYPAf2kCEwaRKsvjr85S+w336w8MJFV6dZVLaATikdCxwLUGpBH9UynCVJc2jaNBg5Ev76V7jjjrze8p57wqGHwsYbu4JUDfM8aEmqRePH5zmxzzsP3ngDllkG/vAHOPhgWHLJoqtTF6hIQKeU7gHuqcRrSVLdSgkeeSS3lq+9Fr74Ar75TTjzTNh1V5jbNlc98d2UpGo3ZQpcfXU+nvzUU/kUqYED86QiTihStwxoSapWr7wC554LF18MH34Iq62WB4Htt18OadU1A1qSqsn06XDrrbkb+9ZbYa658nzYhx6a58d20FfDMKAlqRpMmJBbyueeC6+9BkstBccdl7uye/cuujoVwICWpCI98UQ+tnz11fDZZ7DZZnDCCbD77q653OAMaEmqtGnTYPhwOOssePBBWGABOPDA3I29xhpFV6cqYUBLUqVMmAAXXJCPL7/5Jiy3HJx+el60wpm+1IIBLUnl9txzubV8+eXw6aew1VY5pHfaCbp1K7o6VSkDWpLKYcYMuOmmHMx33gnzzZdPjzr8cFhzzaKrUw0woCWpK02aBJdcAmefnc9j/upX4U9/ylNwLrFE0dWphhjQktQVXn45h/Ill8DHH8NGG8Hxx+dzmLt3L7o61SADWpJmV0q5+/qss3J39txzw4ABcMQRsP76RVenGmdAS9KsmjIlD/j685/zALBeveA3v4Ef/xiWXrro6lQnDGhJ6qxx4/Lo6wsuyHNjr7127tLeZ588CEzqQga0JHVk9Gg47bS8xGNKsNtuuRt7s82cG1tlY0BLUmtmniZ12mlw77159agjjsinSfXtW3R1agAGtCQ19+mnMHRonuFr7FhYdlk49VT44Q+d7UsVZUBLEsD48Xmt5XPOgffeg3XXhSuugL328jQpFcKAltTYxo7NreVLL4XPP8/Tbx51FGyxhceXVSgDWlLjSQnuuy8fX77xRph3XjjgADjySPjGN4quTgIMaEmNZNo0uO66fEz5iSfy1JvHHZeXefzKV4quTvovBrSk+jdpElx0EZx5Zj6XeaWV4Lzzcqu5R4+iq5NaZUBLql9vvJFn+xo8OIf05pvn+bJ33hnmmqvo6qR2GdCS6s/TT8Mpp8A11+TjzXvuCYMGOT+2aooBLak+pAT33w8nngi33AI9e8Jhh+XJRZxYRDXIgJZU22bMgJEjczA//HBeuOL44/PCFYsuWnR10mwzoCXVpqlT4eqr4aST8opSffvmhSwOOsiBX6oLBrSk2jJlSh6RfeqpeUT2GmvkGb8GDMjrMUt1wt9mSbXhww/hL3/Jo7Lffx823TRPy7njjs74pbpkQEuqbm+9BWecAeefD5Mn56k4jzkmB7RUxwxoSdXppZfg5JPhssvyQLB99oGjj4Y11yy6MqkiDGhJ1WX06Dzw629/y3NkDxyYz2FebrmiK5MqyoCWVLyU4K678qlSd9yR110+9th8DrNzZKtBGdCSijNjBtxwA5xwAjz+OCy1VO7WPuQQWGihoquTCmVAS6q86dPzqlJ//CM8+yyssEIeBHbAATDffEVXJ1UFZ4uXVDnTpuVzlldfPQ/6mj49Xx87Nh9rNpylfzOgJZXftGlw6aWw6qqw3355QpFhw3Lr+TvfgW7diq5Qqjp2cUsqny++gKFD4U9/gldfhbXXhuuvh/79Xe5R6oCfEEld7/PP4bzzYMUV4Yc/hMUWgxEj4MknYffdDWepE/yUSOo6n32Wp+NcYYW8mlTv3nDzzfDYY7DLLk7JKc0Cu7glzbkpU2Dw4HyK1Dvv5Gk4hwyBb33LUJZmkwEtafZNnpy7sk85BcaPh622giuvhC22MJilOWRAS5p1H3+c114+7bS8stQ228D//i9stlnRlUl1w4CW1HkTJ8LZZ+fVpT78EHbYIQfzRhsVXZlUdwxoSR2bNAnOOiu3mD/6CHbdFX7zG1h//aIrk+qWAS2pbVOm5K7sk06CCRPy+cv/93+wzjpFVybVPU+zkvRln3/+n9Oljj4a+vXLp0o1NRnOUoXYgpb0H1OnwmWXwe9/D+PGweab5yk5HfwlVZwtaEn/WbRi1VXzzF9LLQW33w733GM4SwUxoKVGllKeG3uttfIiFvPPn6fkfOSRfOqU5zJLhTGgpUaUUp6Cs18/+Pa382pT11wDTz3llJxSlTCgpUZz9915Ks6ddsrnMg8Zkpd9HDDARSykKuKnUWoUDz+c58b+5jfhn//MU3S++CIceGBen1lSVTGgpXr31FOw886w8cbwzDN5FrCXX4ZDDoF55im6OkltMKClevX887DXXrDuuvDQQ3DCCfDqq/Czn8F88xVdnaQO2K8l1Ztx4/L82EOHwgILwHHHwZFHwiKLFF2ZpFlgQEv1YuLE3Eo+66x8fdAg+OUvYYkliq1L0mwxoKVa9/nneb7s44/Po7L33x/+8Afo06foyiTNgbIdg46I+SLisYh4OiKei4jfleu1pIY0YwZceSWsskpuLffrB08+CZdeajhLdaCcLejPgW+mlCZHRHfggYi4JaX0SBlfU2oMd90Fv/hFDuS1187Tcm6zTdFVSepCZWtBp2xy6Wr30k8q1+tJDeGZZ2DHHfP5zO+/nweCPfGE4SzVobKeZhUR3SJiDDAeGJVSerSVbQZGxOiIGP3ee++Vsxypdr35Jnz/+3nO7IcfhlNOgbFj8/zZzv4l1aWyfrJTStNTSmsDywAbRMTqrWwzOKXUL6XUr1evXuUsR6o9H30Exx4LK66YV5v6+c/hlVfgqKM8l1mqcxUZxZ1SmhgR9wDbA89W4jWlmvbFF3DuuXk09oQJuaX8hz9A375FVyapQso5irtXRCxSutwD2Bp4sVyvJ9WFlPKqUt/4Rp7xa+218zHmoUMNZ6nBlLMFvTRwaUR0I/8hMCylNLKMryfVtnvugaOPhscfhzXXhFtvhW23delHqUGVLaBTSn8H1inX80t147nn4JhjYORIWHbZvPzjfvtBt25FVyapQA7/lIrywQdw2GG5tXz//XDSSXlk9oEHGs6SnOpTqrhp02Dw4LygxcSJ8OMfw+9+B4svXnRlkqqIAS1V0j33wE9/micc2WqrvLDFGmsUXZWkKmQXt1QJ//xnXpt5q61g0iS47jq4807DWVKbbEFL5TRlCpx4Yp75a6658rnMgwZBjx5FVyapyhnQUjnMPJ/5F7/I03Tusw+cfHIepS1JnWAXt9TVnnoKttgC9t0XllgC7rsPrrrKcJY0Swxoqau89x4ccgistx688AKcfz6MHg2bbVZ0ZZJqkAEtzampU/No7JVWgosuyqO0X3oJBg70fGZJs81j0NKcGDUqz5n9/PN5TeYzz4RVVy26Kkl1wBa0NDtefRV22y3Plf3ZZ9DUBLfdZjhL6jIGtDQrJk+GX/0qrzZ1xx1wwgm59dy/v4taSOpSdnFLnZESXHstHHkkvP027L9/Pr+5d++iK5NUp2xBSx157TXYaSfYe29Yail46CG47DLDWVJZGdBSW6ZOzZOLrLZaXm3qzDPh0Udho42KrkxSA7CLW2rNww/nc5qfeSYPBvvzn51oRFJF2YKWmps4EX7yE9hkE/jwQxg+PP8YzpIqzICWIA8CGzYsj84+/3w44og8Onu33YquTFKDsotbeu01OPRQuOUWWHddGDkyT9cpSQWyBa3G1dYgMMNZUhWwBa3G5CAwSVXOFrQai4PAJNUIA1qNwUFgkmqMXdyqfw4Ck1SDbEGrfjkITFINm6UWdEQsCiybUvp7meqRusajj8LBBzsITFLN6rAFHRH3RMRCEbEY8DRwSUScXv7SpNnw+edw7LGw8cYOApNU0zrTxb1wSmkSsAdwSUppPWDr8pYlzYannoJ+/fIykAcdBM895yAwSTWrMwE9d0QsDQwARpa5HmnWTZ0Kf/gDbLABvP9+HgR24YWw0EJFVyZJs60zx6B/D9wGPJhSejwilgf+Ud6ypE56/nk48EAYPRr23RfOPhsWX7zoqiRpjnUY0Cmla4Frm11/Ffh2OYuSOjR9eh6V/etfQ8+e+RznvfYquipJ6jKdGSS2UkTcGRHPlq6vGRG/KX9pUhteeQW23BKOOgq22y4fazacJdWZzhyDvgA4FpgKUDrFap9yFiW1KiU491xYc818+tSll0JTEyy5ZNGVSVKX68wx6PlTSo9FRPPbppWpHql1b7wBP/gBjBoF22wDF13kqVOS6lpnWtDvR8QKQAKIiD2Bd8palTRTSrmlvPrq8NBDuQV9222Gs6S615kW9KHAYGCViHgLeA3Yr6xVSQD/+ldeEnLECNh0UxgyBFZYoeiqJKkiOjOK+1Vg64hYAJgrpfRx+ctSw7v2Wvjxj2HyZDjttLz6VLduRVclSRXTYUBHxHEtrgOQUvp9mWpSI5swAQ47DK6+Os8KdtlleYlISWownTkG/Umzn+nADkDfMtakRjVyZD7WfN11eWawhx82nCU1rM50cZ/W/HpEnAqMKFtFajyTJsGRR8LFF8Maa8DNN8M66xRdlSQVanbWg54fWL6rC1GDevjhHMpDhuRVqB5/3HCWJDp3DPoZSqdYAd2AXuT5uaXZlxKcfjocc0w+ZeqBB2CjjYquSpKqRmdOs9q52eVpwLspJScq0ez74AP43vfgxhth991z1/YiixRdlSRVlTYDOiIWK11seVrVQhFBSumD8pWluvXII7D33vDOO3DWWXD44fDfs9RJkmi/Bf0EuWu7tW/PhMehNStSgjPOgF/+EpZZJndpb7BB0VVJUtVqM6BTSstVshDVsQ8/zF3aI0bAbrvlLu1FFy26Kkmqap05Bk1ELAqsCMw387aU0n3lKkp15LHHYMAAeOut3II+4gi7tCWpEzozivuHwBHAMsAYYEPgYeCb5S1NNS2lfIz56KOhd+/cpf0//1N0VZJUMzpzHvQRwPrAP1NKWwHrAO+VtSrVtg8/hD32yJOP7LADPPmk4SxJs6gzAf1ZSukzgIiYN6X0IrByectSzXr8cVh33Txt52mnQVMTLLZYx4+TJP2XzhyDfjMiFgGagFER8SHwdnnLUs1JCc4+G446CpZeGu6/HzbcsOiqJKlmdWYu7t1LF38bEXcDCwO3lrUq1ZaJE+EHP4Drr4dddsnTdtpqlqQ50t5EJTcBVwJNKaVPAFJK91aqMNWI0aPzKO033oBTT4Wf/9xR2pLUBdo7Bj2YPM3n6xFxTUTsFhHzVKguVbuU4C9/gU02gWnT4L77YNAgw1mSukibAZ1SuiGltC/QB7geOBAYFxEXR8Q2lSpQVeijj3Kr+fDDYZtt4KmnXOhCkrpYh6O4U0qfppSuKR2L3pZ8mpXHoBvVk0/mUdrDh8PJJ+fZwRZfvOiqJKnudBjQEbFkRBweEQ+SR3LfDqxX9spUfS65JLeUv/gid2n/4hcw1+wsKS5J6kib364RcXBE3AU8CawEHJ1SWj6l9MuU0piOnjgilo2IuyPihYh4LiKO6MK6VUkzZsCxx8L3vw+bb567tDfeuOiqJKmutXea1cbAicAdKaUZs/Hc04BBKaUnI2JB4ImIGJVSen52ClVBPv0UDjgArrsODjkkn+vcvXvRVUlS3WtvNauD5uSJU0rvAO+ULn8cES8AXwUM6Frx7ruw6655drDTTstTdzpKW5IqolOrWc2piOhLHlz2aCv3DQQGAvTp06cS5agznn0Wdt4Z3nsvT0Cy225FVyRJDaW9Y9A3l4J1jkRET+BvwM9SSpNa3p9SGpxS6pdS6terV685fTl1hdtuy+c3zxwMZjhLUsW1NwR3CHB7RPw6ImbroGPpcX8DrkgpXT87z6EKO+882GknWG65vJbzeg7Yl6QitHcMelhpus/jgNERMRSY0ez+09t74ogI4CLghY62VRWYPj2fNnXGGTmgr7oKFlyw6KokqWF1dBLrVOATYF5gwRY/HdkE2B/4ZkSMKf3sOCfFqkwmT87rN59xBvz0p3DDDYazJBWsvcUytgdOB0YA66aUpszKE6eUHgAc8lvt3norr0D19NP5FKrDDiu6IkkS7Y/i/jWwV0rpuUoVowobMyaP1P7oI7jxRtjRDg5JqhbtHYPerJKFqMJGjoR99snrNj/4IKy5ZtEVSZKacSLlRpMSnHUW9O8Pq6wCjz5qOEtSFTKgG8m0aXmJyJ/9LAf0vffC0ksXXZUkqRUGdKOYNClP2/nXv+bTqa67DhZYoOiqJEltqMhUnyrYuHF5MNjzz8PgwXDwwUVXJEnqgAFd7x5/PJ9G9dlncOutsPXWRVckSeoEu7jr2fXXwxZbQI8e8NBDhrMk1RADul6dfjp8+9uw1lp5pPaqqxZdkSRpFhjQ9eiUU2DQINhzT7jrLvjKV4quSJI0izwGXW9OPx2OPjpPQjJ0KMztWyxJtcgWdD0588zcct5rL8NZkmqcAV0vzj4bjjwyH3e+4grDWZJqnAFdD845Jy8TudtueR3n7t2LrkiSNIcM6Fp3/vlw6KF5lrBrrjGcJalOGNC17IIL4Ec/gp12gmHDYJ55iq5IktRFDOhadfHFMHAg7LAD/O1vMO+8RVckSepCBnQtuvRS+OEPYbvt8mxhhrMk1R0DutZcfjkcdFCetnP4cJhvvqIrkiSVgQFdS668Eg48ELbaCpqa8hzbkqS6ZEDXimuugf33h803hxtvhPnnL7oiSVIZGdC14Npr4bvfhU02gZEjDWdJagAGdLW7/nrYd1/YcEO4+WZYYIGiK5IkVYABXc2ammDvvWGDDeCWW6Bnz6IrkiRViAFdrW68EQYMgPXWg1tvhQUXLLoiSVIFGdDV6Kab8qIXa68Nt90GCy1UdEWSpAozoKvNLbfAHnvAmmvC7bfDwgsXXZEkqQAGdDW5/XbYfXdYbbV8eZFFiq5IklQQA7pa3HEH9O8Pq6wCo0bBYosVXZEkqUAGdDW46668XOSKK+agXnzxoiuSJBXMgC7amDGwyy6w/PJw552wxBJFVyRJqgIGdJE++gj22isfa77jDujVq+iKJElVYu6iC2hYKeUlI197De65B5ZaquiKJElVxIAuyl/+AtddByefDJtuWnQ1kqQqYxd3ER59FAYNyseeBw0quhpJUhUyoCvtgw/yFJ69e8OQITCXb4Ek6cvs4q6kGTPgwAPhnXfggQc811mS1CYDupJOPTWv5/znP+cVqiRJaoP9q5Vy//3wq1/BnnvCYYcVXY0kqcoZ0JUwfjzssw8stxxceCFEFF2RJKnK2cVdbtOnw3e/CxMm5GUkXZ1KktQJBnS5HX98niVs8OC8vrMkSZ1gF3c53Xkn/Pa3sN9+edYwSZI6yYAul7ffhu98Jy8fee65HneWJM0Su7jLYdo02HdfmDwZ7r4bevYsuiJJUo0xoMvhuOPgvvtg6FBYddWiq5Ek1SC7uLvazTfDCSfAwQfnY8+SJM0GA7orjRsH++8Pa60FZ51VdDWSpBpmQHeVL76AvfeGqVPh2muhR4+iK5Ik1TCPQXeVY46BRx6BYcNgxRWLrkaSVONsQXeF4cPhjDPg8MNhr72KrkaSVAcM6Dn1yitw0EGw/vpwyilFVyNJqhMG9Jz47DMYMCBPQjJsGMw7b9EVSRpgp50AAA4aSURBVJLqhMeg58TPfw5PPgk33AB9+xZdjSSpjtiCnl1XXZWn8PzFL2DXXYuuRpJUZwzo2fHii3kikk02yatVSZLUxQzoWTVlSh6p3aMHXH01dO9edEWSpDpUtoCOiIsjYnxEPFuu1yjEYYfBc8/BFVfAMssUXY0kqU6VswU9BNi+jM9feddcA5dcAr/5DWy7bdHVSJLqWNkCOqV0H/BBuZ6/EIMHw0orwf/9X9GVSJLqnMegO+uDD+Dee+Hb34Zu3YquRpJU5woP6IgYGBGjI2L0e++9V3Q5bRs5EqZPh912K7oSSVIDKDygU0qDU0r9Ukr9evXqVXQ5bWtqgt69oV+/oiuRJDWAwgO6JkyZArfemlvPc/lfJkkqv3KeZnUV8DCwckS8GRE/KNdrld2oUfDpp3ZvS5IqpmxzcaeU9i3Xc1dcUxMsvDBsuWXRlUiSGoT9tR2ZNg1uvBF23tlZwyRJFWNAd+SBB2DCBLu3JUkVZUB3pKkpr/O8fX1NiiZJqm4GdHtSguHDYZttoGfPoquRJDUQA7o9Y8bAuHGw++5FVyJJajAGdHuamvJ5z7vsUnQlkqQGY0C3Z/hw2GQTqOYZziRJdcmAbssrr8Azz9i9LUkqhAHdlqam/K+nV0mSCmBAt6WpCdZaC5ZbruhKJEkNyIBuzfjx8OCDtp4lSYUxoFszYkQ+B9qAliQVxIBuTVMT9O2bu7glSSqAAd3Sxx/DHXfk1nNE0dVIkhqUAd3SrbfC5597epUkqVAGdEtNTbDEErDxxkVXIklqYAZ0c198ATfdlKf2nHvuoquRJDUwA7q5e+6Bjz6ye1uSVDgDurmmJlhgAdh666IrkSQ1OAN6phkzckBvvz306FF0NZKkBmdAz/T44/DOO05OIkmqCgb0TE1NeWDYTjsVXYkkSQb0vw0fDltuCYsuWnQlkiQZ0AC8+CKMHWv3tiSpahjQkFvPAP37F1uHJEklBjTk48/rrw/LLFN0JZIkAQY0vPUWPPaY3duSpKpiQN9wQ/7X2cMkSVXEgG5qgpVWglVWKboSSZL+rbEDeuJEuPtu136WJFWdxg7om26CadPs3pYkVZ3GDuimJlh6adhgg6IrkSTpvzRuQH/6KdxySz73ea7G/W+QJFWnxk2mO++ETz7x9CpJUlVq3IBuaoKFFoKttiq6EkmSvqQxA3r6dBgxIq9cNc88RVcjSdKXNGZAP/QQvPee3duSpKrVmAHd1JRbzjvsUHQlkiS1qvECOqW8etXWW8OCCxZdjSRJrWq8gH7mGXjtNbu3JUlVrfECevjwPK3nrrsWXYkkSW1qvIBuaoKNN4Yllyy6EkmS2tRYAf366zBmjHNvS5KqXmMFdFNT/rd//2LrkCSpA40X0KuvDl//etGVSJLUrsYJ6Pffh/vvt3tbklQTGiegb7wRZszw9CpJUk1onIBuaoI+fWCddYquRJKkDjVGQH/yCdx+e249RxRdjSRJHWqMgL7tNvjsM7u3JUk1ozECuqkJFlsMNtus6EokSeqU+g/oqVPzALFddoG55y66GkmSOqX+A/q++2DiRLu3JUk1pf4DuqkJevSAbbctuhJJkjqtvgM6pRzQ220H889fdDWSJHVafQf0E0/Am286e5gkqebUd0APHw7dusFOOxVdiSRJs6S+A7qpCTbfHBZfvOhKJEmaJWUN6IjYPiLGRsTLEXFMOV/rS156CZ5/3u5tSVJNKltAR0Q34K/ADsCqwL4RsWq5Xu9LXPtZklTDytmC3gB4OaX0akrpC+BqoHJp2dQE662XF8iQJKnGlHNqra8CbzS7/ibwPy03ioiBwECAPl0VptOnwwor5ICWJKkGlTOgW1s2Kn3phpQGA4MB+vXr96X7Z0u3bjB0aJc8lSRJRShnF/ebwLLNri8DvF3G15MkqW6UM6AfB1aMiOUiYh5gH2BEGV9PkqS6UbYu7pTStIg4DLgN6AZcnFJ6rlyvJ0lSPSnr+osppZuBm8v5GpIk1aP6nklMkqQaZUBLklSFDGhJkqqQAS1JUhUyoCVJqkIGtCRJVciAliSpChnQkiRVIQNakqQqFCl1zQJSXSEi3gP+2YVPuQTwfhc+X5HqZV/qZT/AfalW9bIv9bIf4L6052sppV6t3VFVAd3VImJ0Sqlf0XV0hXrZl3rZD3BfqlW97Eu97Ae4L7PLLm5JkqqQAS1JUhWq94AeXHQBXahe9qVe9gPcl2pVL/tSL/sB7stsqetj0JIk1ap6b0FLklST6iKgI2L7iBgbES9HxDGt3D9vRFxTuv/RiOhb+SrbFxHLRsTdEfFCRDwXEUe0ss2WEfFRRIwp/RxXRK2dERGvR8QzpTpHt3J/RMSfS+/J3yNi3SLq7EhErNzs/3tMREyKiJ+12KZq35eIuDgixkfEs81uWywiRkXEP0r/LtrGYw8sbfOPiDiwclW3Wktr+3FKRLxY+v0ZHhGLtPHYdn8XK62NffltRLzV7HdoxzYe2+53XaW1sS/XNNuP1yNiTBuPrZr3pa3v38I/Kymlmv4BugGvAMsD8wBPA6u22OYnwHmly/sA1xRddyv7sTSwbunygsBLrezHlsDIomvt5P68DizRzv07ArcAAWwIPFp0zZ3Yp27Av8jnLdbE+wJsDqwLPNvstpOBY0qXjwFOauVxiwGvlv5dtHR50Srbj22BuUuXT2ptP0r3tfu7WCX78lvgqA4e1+F3XTXsS4v7TwOOq/b3pa3v36I/K/XQgt4AeDml9GpK6QvgaqB/i236A5eWLl8HfCsiooI1diil9E5K6cnS5Y+BF4CvFltVWfUHLkvZI8AiEbF00UV14FvAKymlrpxMp6xSSvcBH7S4ufnn4VJgt1Yeuh0wKqX0QUrpQ2AUsH3ZCu1Aa/uRUro9pTStdPURYJmKFzYb2nhPOqMz33UV1d6+lL5jBwBXVbSo2dDO92+hn5V6COivAm80u/4mXw62f29T+kB/BCxekepmQ6kLfh3g0Vbu3igino6IWyJitYoWNmsScHtEPBERA1u5vzPvW7XZh7a/bGrlfQFYMqX0DuQvJuArrWxTa+/P98k9Mq3p6HexWhxW6q6/uI2u1Fp7TzYD3k0p/aON+6vyfWnx/VvoZ6UeArq1lnDLoemd2aYqRERP4G/Az1JKk1rc/SS5e3Ut4GygqdL1zYJNUkrrAjsAh0bE5i3ur5n3BCAi5gF2Ba5t5e5ael86q2ben4j4NTANuKKNTTr6XawG5wIrAGsD75C7hluqmfekZF/abz1X3fvSwfdvmw9r5bYueV/qIaDfBJZtdn0Z4O22tomIuYGFmb0uprKKiO7kX44rUkrXt7w/pTQppTS5dPlmoHtELFHhMjslpfR26d/xwHBy91xznXnfqskOwJMppXdb3lFL70vJuzMPJ5T+Hd/KNjXx/pQG5OwMfDeVDgi21InfxcKllN5NKU1PKc0ALqD1GmviPYF/f8/uAVzT1jbV9r608f1b6GelHgL6cWDFiFiu1MrZBxjRYpsRwMyRdXsCd7X1YS5K6XjNRcALKaXT29hmqZnHziNiA/L7N6FyVXZORCwQEQvOvEwezPNsi81GAAdEtiHw0cyupCrVZmugVt6XZpp/Hg4Ebmhlm9uAbSNi0VJ367al26pGRGwP/BLYNaU0pY1tOvO7WLgW4y92p/UaO/NdVy22Bl5MKb3Z2p3V9r608/1b7Gel6NFzXfFDHhH8EnmE469Lt/2e/MEFmI/cNfky8BiwfNE1t7IPm5K7Rf4OjCn97Aj8CPhRaZvDgOfIozcfATYuuu429mX5Uo1Pl+qd+Z4035cA/lp6z54B+hVddzv7Mz85cBdudltNvC/kPyreAaaS/9L/AXn8xZ3AP0r/Llbath9wYbPHfr/0mXkZOKgK9+Nl8rG/mZ+XmWdq9AZubu93sQr3ZWjpc/B3cigs3XJfSte/9F1XbftSun3IzM9Hs22r9n1p5/u30M+KM4lJklSF6qGLW5KkumNAS5JUhQxoSZKqkAEtSVIVMqAlSapCBrRUQ0qr7rwWEYuVri9auv61FtvdExHbtbjtZxFxTgfPP7nrq5Y0OwxoqYaklN4gTwt5YummE4HB6csLeFxFnsiiufbmEpdUZQxoqfacAWwYeV3qTWl93ubrgJ0jYl749wIAvYEHIqJnRNwZEU+W1uP90opIkde4Htns+l8i4nuly+tFxL2lRQ5uazYV4k8j4vnSgg9Xd+0uS41n7qILkDRrUkpTI+IXwK3AtikvPdhymwkR8Rh52bsb+M866CkiPgN2TylNKs0Z/khEjEidmLWoNF/x2UD/lNJ7EbE3cDx5JqVjgOVSSp9HxCJdtb9So7IFLdWmHchTLK7ezjbNu7mbd28H8KeI+DtwB3lpvCU7+borl15zVESMAX7Df9Zh/jtwRUTsR15dStIcsAUt1ZiIWBvYBtiQ3GV9dWp9oZEm4PSIWBfokUoL0gPfBXoB65Va46+T56tvbhr//Qf8zPsDeC6ltFErr7cTsDl5Wc7/jYjVUl5/XdJssAUt1ZDSqjvnkterHQecApza2rYpL4F5D3Ax/z04bGFgfCmctwK+1srD/wmsGhHzRsTCwLdKt48FekXERqV6ukfEahExF7BsSulu4GhgEaDnnO2t1NgMaKm2HAyMSymNKl0/B1glIrZoY/urgLWA5oO2rgD6RcRocmv6xZYPKo0WH0ap2xp4qnT7F+QlW0+KiKfJq/5sDHQDLo+IZ0rbnpFSmjgnOyo1OlezkiSpCtmCliSpChnQkiRVIQNakqQqZEBLklSFDGhJkqqQAS1JUhUyoCVJqkIGtCRJVej/AZAhL3Hz5i/KAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import numpy as np  \n",
    "import math  \n",
    "   \n",
    "x_vals = np.linspace(0, 20, 20)  \n",
    "y_vals = [math.sqrt(i) for i in x_vals]  \n",
    "plt.xlabel('X Values')  \n",
    "plt.ylabel('Y Values')  \n",
    "plt.title('Square Roots')  \n",
    "plt.plot(x_vals, y_vals, 'r')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x15a70239e88>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAegAAAGDCAYAAADgY4OVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nO3dd3hUVf7H8ffX0It0CyILKkVAiBAUFSkr2EDBBqgo666gu3ZRV9ddfpZ1bShYVjEqVaWIEoqKgopYACniCggqooCy0pu0JJzfH2fQbEwnM/fOzOf1PHnIzNzM/d5MZj6cc889x5xziIiISLgcEnQBIiIi8lsKaBERkRBSQIuIiISQAlpERCSEFNAiIiIhpIAWEREJIQW0iIhICCmgRWLEzNqb2Sdmts3MNpvZx2bWNui6CmNmfzCzbDPbaWbbzexzM+teSs890sz+WRrPJZJoFNAiMWBmhwLTgKeAmsBRwL3A3gBqSSnBj81xzlUBqgPPAOPMrHrpViYiOSmgRWKjMYBzbqxzLts5t9s5945z7j/gQ9PMBpvZRjP71syuMzNnZmUij39nZl0OPJmZ3WNmL+W4/aqZ/TfSOp9tZs1zPDbSzJ41szfN7Gegs5mVj+xvtZn9ZGbDzKxiYQfhnNsPjAEqA41y7ON8M1tqZlvNbJaZHZ/jseMj922NbHN+5P4BwOXAHZHW+dTI/X81sx/MbIeZrTCzM0r2KxeJbwpokdj4Csg2s1Fmdo6Z1cj1eH+gO3AikAZcXMznfwsfmIcBi4CXcz1+GfAAUBX4CHgY/5+GVOA4fIt+UGE7ibS+rwIyge8j9zUGxgI3A3WAN4GpZlbOzMoCU4F3IrXdALxsZk2cc+mROh9xzlVxzp1nZk2A64G2zrmqwFnAd8X8XYgkBAW0SAw457YD7QEHPA9sMLMpZnZ4ZJNewFDn3Brn3GbgwWI+/3Dn3A7n3F7gHqCVmVXLsclk59zHkRbwXvx/CG5xzm12zu0A/gX0KWAX7cxsK7AHGAz0dc6tjzzWG3jDOTfDOZcZebwicCrQDqgCPOSc2+ecew/f1X9pPvvJBsoDzcysrHPuO+fcyuL8LkQShQJaJEacc1865/7gnKsHtADqAkMjD9cF1uTY/PuiPm+ke/whM1tpZtv5tcVZO8dmOZ+7DlAJWBjpdt4KTI/cn5+5zrnqQA1gCnB6jsfq5qw38p+ANfhWeV1gTeS+nMd2VF47cc59g2+J3wOsN7NxZla3gLpEEpYCWiQAzrnlwEh8UAOsA47OsUn9XD/yMz5UDzgix/eXAT2ALkA1oEHkfsu5yxzfbwR2A82dc9UjX9Uig8AKq3sn8BfgCjM7MXL3j8DvDmxjZhY5lh8ijx1tZjk/a+pHHstd14F9vOKcax95TofvjhdJOgpokRgws6ZmNtDM6kVuH43v5p0b2WQCcKOZ1Yucn74z11MsBvqYWVkzy32Ouiq+23oTPsT/VVAtkdbs88AQMzssUs9RZnZWUY7FObcJeIFfz1lPALqZ2RmRc84DI/V8AszD/+fijkjtnYDzgHGRn/0JOObAc5tZEzP7vZmVx3en78Z3e4skHQW0SGzsAE4G5kVGUs8FluDDDHxgvg18jh/k9Xqun/8HcCywBX951is5HhuN7zb+AVjGr6FfkL8C3wBzI93iM4EmxTieocC5ZtbSObcC6Iu/hGwjPoDPi5xz3gecD5wTeewZ4MpIDwLAi/jzzVvNLAN//vmhyLb/xQ8s+1sx6hJJGObcb3qYRCRgZtYAWAWUdc5lBVuNiARBLWgREZEQUkCLiIiEkLq4RUREQkgtaBERkRBSQIuIiIRQmaALyKl27dquQYMGQZchIiISEwsXLtzonMtzFr9QBXSDBg1YsGBB0GWIiIjEhJnlO62vurhFRERCSAEtIiISQgpoERGREArVOWiReJSZmcnatWvZs2dP0KUkpQoVKlCvXj3Kli0bdCkipUoBLXKQ1q5dS9WqVWnQoAF+pUWJFeccmzZtYu3atTRs2DDockRKlbq4RQ7Snj17qFWrlsI5AGZGrVq11HshCUkBLVIKFM7B0e9eEpUCWiQBPPDAAzRv3pyWLVuSmprKvHnzgi4JgHvuuYejjjqK1NRUmjVrxtixY0v8XCNHjuTHH38sxepEwk3noEXi3Jw5c5g2bRqLFi2ifPnybNy4kX379kV1n9nZ2aSkpBRp21tuuYXbbruNr7/+mjZt2nDxxReXaEDXyJEjadGiBXXr1i32z4rEI7WgReLcunXrqF27NuXLlwegdu3av4TY9OnTadq0Ke3bt+fGG2+ke/fugG/ZDh48+JfnaNGiBd999x0APXv2pE2bNjRv3pz09PRftqlSpQqDBg3i5JNPZs6cOSxcuJCOHTvSpk0bzjrrLNatW1dgnY0aNaJSpUps2bIFgMWLF9OuXTtatmzJBRdcUOD9EydOZMGCBVx++eWkpqaye/fu0vnliYSYWtAipenmm2Hx4tJ9ztRUGDo034fPPPNM7rvvPho3bkyXLl3o3bs3HTt2ZM+ePfTv35/33nuP4447jt69exdpd8OHD6dmzZrs3r2btm3bctFFF1GrVi1+/vlnWrRowX333UdmZiYdO3Zk8uTJ1KlTh/Hjx3P33XczfPjwfJ930aJFNGrUiMMOOwyAK6+8kqeeeoqOHTsyaNAg7r33XoYOHZrv/U8//TSDBw8mLS2teL8/kTilFrRInKtSpQoLFy4kPT2dOnXq0Lt3b0aOHMny5ctp2LAhjRo1wszo27dvkZ7vySefpFWrVrRr1441a9bw9ddfA5CSksJFF10EwIoVK1iyZAldu3YlNTWVf/7zn6xduzbP5xsyZAhNmjTh5JNP5p577gFg27ZtbN26lY4dOwLQr18/Zs+ene/9IoHLzoYZMyCfv/NoUAtapDQV0NKNppSUFDp16kSnTp044YQTGDVqFKmpqfmOcC5Tpgz79+//5faBy5RmzZrFzJkzmTNnDpUqVaJTp06/PFahQoVfzjs752jevDlz5swptLYD56Bff/11rrzySlauXHmwhysSO19+CaNGwUsvwQ8/wH33wT/+EZNdqwUtEudWrFjxSysX/Dnc3/3udzRt2pRVq1b9Eog5R1A3aNCARYsWAb7redWqVYBv2daoUYNKlSqxfPly5s6dm+c+mzRpwoYNG34J6MzMTJYuXVpgnRdeeCFpaWmMGjWKatWqUaNGDT788EMAxowZQ8eOHfO9H6Bq1ars2LGj2L8fkWLbtAn+/W846SRo1gwGD/anmsaPh9tvj1kZakGLxLmdO3dyww03sHXrVsqUKcNxxx1Heno6FSpUID09nW7dulG7dm3at2/PkiVLALjooosYPXo0qamptG3blsaNGwNw9tlnM2zYMFq2bEmTJk1o165dnvssV64cEydO5MYbb2Tbtm1kZWVx880307x58wJrHTRoEJdddhn9+/dn1KhRXHvttezatYtjjjmGESNGAOR7/x/+8AeuvfZaKlasyJw5c6hYsWJp/QpFYN8+eOst31qeNg0yM6FlS3jsMbjsMjjiiJiXZM65mO80P2lpaU7rQUu8+fLLLzn++OODLqNQs2bNYvDgwUybNi3oUkpdvLwGEjLOwaJFMHo0vPIKbNwIhx0Gl18O/fpBq1ZRL8HMFjrn8hz5qBa0iIgklx9/hJdf9q3lpUuhXDno0cOH8plnQkgWXlFAiySJA4PIRJLS7t2QkeFDecYM2L8f2rWDZ5+F3r2hRo2gK/wNBbSIiCQm5+Djj30oT5gA27dD/fpw111w5ZUQGXsRVgpokVLgnNOiDQEJ0zgaCYnvvvPnlUePhpUroXJluPhi34XdsSMcEh8XMCmgRQ5ShQoV2LRpk5acDMCB9aArVKgQdCkStF27YNIkGD4c3nsPzKBzZxg0CC68EKpUCbrCYlNAixykevXqsXbtWjZs2BB0KUmpQoUK1KtXL+gyJAjOwaefwogRMHas78I+5hg/mUi/fr47O44poEUOUtmyZWnYsGHQZYgkj59+gjFjfDAvWwYVK8Ill8BVV0GHDnHThV0YBbSIiIRfZia88YYP5Tfe8HNjn3IKPP889OoFhx4adIWlTgEtIiLhtWSJD+WXXoL16/2MXgMH+tZy06ZBVxdVCmgREQmXrVv9OeURI2D+fD9xyHnn+VA++2wokxzRlRxHKSIi4bZ/vx99PXy4H429Zw+ccAIMGeKn3qxTJ+gKY04BLSIiwVm1CkaO9F+rV0P16vCnP/nWcuvW/nKpJKWAFhGR2Nq710+7+cILMHOmD+GuXeGRR/yc2LquHVBAi4hIrCxb5kN59Gi/5nL9+nDvvb61fPTRQVcXOgpoERGJnp9/9vNgv/ACfPKJH/DVowf07w9nnAEpKUFXGFoKaBERKV0H1ll+/nm/zvKOHdCkCQweDFdc4ddclkIpoEVEpHRs3erXWX7hBVi82M/w1asXXH01nHZaUg/4KgkFtIiIlJxz8NFHvrX86qv+8qgTT4RnnoFLL/WjsqVEFNAiIlJ869f7dZZfeAG++spPtXnVVb613Lp10NUlBAW0iIgUTXY2zJjhQ3nyZMjKgvbt4W9/8+stV64cdIUJRQEtIiIFW7cOXnzRd2OvXg21a8NNN/kJRY4/PujqEpYCWkREfmv/fnj3XRg2zLeWs7OhSxc/ErtHDyhXLugKE54CWkREfrV+vZ9287nn4NtvfWv51lthwAA47rigq0sqCmgRkWTnHHzwgQ/l117zay936AD//CdceCGULx90hUkp6gFtZinAAuAH51z3aO9PRESKaPNmPxL7uedgxQp/SdRf/gLXXKNzyyEQixb0TcCXwKEx2JeIiBTEOZgzx59bnjDBL1zRrp3v1u7Vy08uIqEQ1YA2s3pAN+AB4NZo7ktERAqwbRu89JIP5iVLoGpV+OMffWu5Vaugq5M8RLsFPRS4A6ga5f2IiEheFizwoTx2LOza5ScRSU/3s3xVqRJ0dVKAqAW0mXUH1jvnFppZpwK2GwAMAKhfv360yhERSR47d/pAHjbML1pRqZIP5GuvhbS0oKuTIopmC/o04HwzOxeoABxqZi855/rm3Mg5lw6kA6Slpbko1iMikthWrPBzYI8cCdu3Q4sW8PTT0LcvVKsWdHVSTFELaOfcXcBdAJEW9G25w1lERA5SVhZMmwb//jfMnOnXW774YrjuOjj1VK0gFcd0HbSISDxav97PiT1sGKxZA/Xqwf33Q//+cPjhQVcnpSAmAe2cmwXMisW+REQSlnMwd65vLb/6KuzbB7//PQwdCuefD2XU5kokejVFRMJu1y4YN86fT/7sM3+J1IABflIRTSiSsBTQIiJhtXIlPPssDB8OW7ZA8+Z+EFjfvj6kJaEpoEVEwiQ7G6ZP993Y06fDIYf4+bCvu87Pj61BX0lDAS0iEgabNvmW8rPPwqpVcMQRMGiQ78quWzfo6iQACmgRkSAtXOjPLY8bB3v2wOmnw4MPwgUXaM3lJKeAFhGJtawsmDQJnngCPv4YKleGfv18N/YJJwRdnYSEAlpEJFY2bYLnn/fnl9euhYYN4fHH/aIVmulLclFAi4hE29KlvrX80kuwezd07uxDuls3SEkJujoJKQW0iEg07N8Pb7zhg/ndd6FCBX951A03QMuWQVcncUABLSJSmrZvhxEj4Kmn/HXMRx0F//qXn4Kzdu2gq5M4ooAWESkN33zjQ3nECNixA045BR54wF/DXLZs0NVJHFJAi4iUlHO++/qJJ3x3dpky0KsX3HQTtG0bdHUS5xTQIiLFtWuXH/D15JN+AFidOvD3v8Of/wxHHhl0dZIgFNAiIkW1erUfff38835u7NRU36Xdp48fBCZSihTQIiKFWbAAHnvML/HoHPTs6buxTz9dc2NL1CigRUTycuAyqccegw8+8KtH3XSTv0yqQYOgq5MkoIAWEclp924YM8bP8LViBRx9NAweDFdfrdm+JKYU0CIiAOvX+7WWn3kGNmyA1q3h5Zfhkkt0mZQEQgEtIsltxQrfWh41Cvbu9dNv3nYbdOyo88sSKAW0iCQf52D2bH9+eepUKF8errwSbrkFjj8+6OpEAAW0iCSTrCyYONGfU1640E+9OWiQX+bxsMOCrk7kfyigRSTxbd8OL74IQ4f6a5kbN4Zhw3yruWLFoKsTyZMCWkQS15o1frav9HQf0h06+Pmyu3eHQw4JujqRAimgRSTxfP45PPoojB/vzzdffDEMHKj5sSWuKKBFJDE4Bx9+CA89BG+9BVWqwPXX+8lFNLGIxCEFtIjEt/37Ydo0H8xz5viFKx54wC9cUaNG0NWJlJgCWkTiU2YmjBsHDz/sV5Rq0MAvZHHVVRr4JQlBAS0i8WXXLj8ie/BgPyL7hBP8jF+9evn1mEUShP6aRSQ+bNkCTz/tR2Vv3Ajt2/tpOc89VzN+SUJSQItIuP3wAwwZAs89Bzt3+qk477zTB7RIAlNAi0g4ffUVPPIIjB7tB4L16QN33AEtWwZdmUhMKKBFJFwWLPADv157zc+RPWCAv4a5YcOgKxOJKQW0iATPOXjvPX+p1MyZft3lu+7y1zBrjmxJUgpoEQnO/v0weTI8+CDMnw9HHOG7ta+5Bg49NOjqRAKlgBaR2MvO9qtK/fOfsGQJHHusHwR25ZVQoULQ1YmEgmaLF5HYycry1yy3aOEHfWVn+9srVvhzzQpnkV8ooEUk+rKyYNQoaNYM+vb1E4pMmOBbz5ddBikpQVcoEjrq4haR6Nm3D8aMgX/9C779FlJT4fXXoUcPLfcoUgi9Q0Sk9O3dC8OGQaNGcPXVULMmTJkCixbBBRconEWKQO8SESk9e/b46TiPPdavJlW3Lrz5Jnz6KZx3nqbkFCkGdXGLyMHbtQvS0/0lUuvW+Wk4R46EM85QKIuUkAJaREpu507flf3oo7B+PXTuDK+8Ah07KphFDpICWkSKb8cOv/byY4/5laW6doV//ANOPz3oykQShgJaRIpu61Z46im/utSWLXDOOT6YTzkl6MpEEo4CWkQKt307PPGEbzFv2wbnnw9//zu0bRt0ZSIJSwEtIvnbtct3ZT/8MGza5K9f/r//gxNPDLoykYSny6xE5Lf27v31cqk77oC0NH+pVEaGwlkkRtSCFpFfZWbC6NFw332wejV06OCn5NTgL5GYUwtaRH5dtKJZMz/z1xFHwDvvwKxZCmeRgCigRZKZc35u7Fat/CIWlSr5KTnnzvWXTulaZpHAKKBFkpFzfgrOtDS46CK/2tT48fDZZ5qSUyQkFNAiyeb99/1UnN26+WuZR470yz726qVFLERCRO9GkWQxZ46fG/v3v4fvv/dTdC5fDv36+fWZRSRUFNAiie6zz6B7dzj1VPjiCz8L2DffwDXXQLlyQVcnIvlQQIskqmXL4JJLoHVr+OQTePBB+PZbuPlmqFAh6OpEpBDq1xJJNKtX+/mxx4yBypVh0CC45RaoXj3oykSkGBTQIoli61bfSn7iCX974ED461+hdu1g6xKRElFAi8S7vXv9fNkPPOBHZV9xBdx/P9SvH3RlInIQonYO2swqmNmnZva5mS01s3ujtS+RpLR/P7zyCjRt6lvLaWmwaBGMGqVwFkkA0WxB7wV+75zbaWZlgY/M7C3n3Nwo7lMkObz3Htx+uw/k1FQ/LWfXrkFXJSKlKGotaOftjNwsG/ly0dqfSFL44gs491x/PfPGjX4g2MKFCmeRBBTVy6zMLMXMFgPrgRnOuXl5bDPAzBaY2YINGzZEsxyR+LV2Lfzxj37O7Dlz4NFHYcUKP3+2Zv8SSUhRfWc757Kdc6lAPeAkM2uRxzbpzrk051xanTp1olmOSPzZtg3uugsaNfKrTd16K6xcCbfdpmuZRRJcTEZxO+e2mtks4GxgSSz2KRLX9u2DZ5/1o7E3bfIt5fvvhwYNgq5MRGIkmqO465hZ9cj3FYEuwPJo7U8kITjnV5U6/ng/41dqqj/HPGaMwlkkyUSzBX0kMMrMUvD/EZjgnJsWxf2JxLdZs+COO2D+fGjZEqZPhzPP1NKPIkkqagHtnPsPcGK0nl8kYSxdCnfeCdOmwdFH++Uf+/aFlJSgKxORAGn4p0hQNm+G66/3reUPP4SHH/Yjs/v1UziLiKb6FIm5rCxIT/cLWmzdCn/+M9x7L9SqFXRlIhIiCmiRWJo1C2680U840rmzX9jihBOCrkpEQkhd3CKx8P33fm3mzp1h+3aYOBHefVfhLCL5UgtaJJp27YKHHvIzfx1yiL+WeeBAqFgx6MpEJOQU0CLRcOB65ttv99N09ukDjzziR2mLiBSBurhFSttnn0HHjnDppVC7NsyeDWPHKpxFpFgU0CKlZcMGuOYaaNMGvvwSnnsOFiyA008PujIRiUMKaJGDlZnpR2M3bgwvvuhHaX/1FQwYoOuZRaTEdA5a5GDMmOHnzF62zK/JPHQoNGsWdFUikgDUghYpiW+/hZ49/VzZe/ZARga8/bbCWURKjQJapDh27oS//c2vNjVzJjz4oG899+ihRS1EpFSpi1ukKJyDV1+FW26BH3+EK67w1zfXrRt0ZSKSoNSCFinMqlXQrRv07g1HHAGffAKjRyucRSSqFNAi+cnM9JOLNG/uV5saOhTmzYNTTgm6MhFJAuriFsnLnDn+muYvvvCDwZ58UhONiEhMqQUtktPWrfCXv8Bpp8GWLTBpkv9SOItIjCmgRcAPApswwY/Ofu45uOkmPzq7Z8+gKxORJKUubpFVq+C66+Ctt6B1a5g2zU/XKSISILWgJXnlNwhM4SwiIaAWtCQnDQITkZBTC1qSiwaBiUicUEBLctAgMBGJM+rilsSnQWAiEofUgpbEpUFgIhLHitWCNrMawNHOuf9EqR6R0jFvHvTvr0FgIhK3Cm1Bm9ksMzvUzGoCnwMjzOzx6JcmUgJ798Jdd8Gpp2oQmIjEtaJ0cVdzzm0HLgRGOOfaAF2iW5ZICXz2GaSl+WUgr7oKli7VIDARiVtFCegyZnYk0AuYFuV6RIovMxPuvx9OOgk2bvSDwF54AQ49NOjKRERKrCjnoO8D3gY+ds7NN7NjgK+jW5ZIES1bBv36wYIFcOml8NRTUKtW0FWJiBy0QgPaOfcq8GqO298CF0WzKJFCZWf7Udl33w1VqvhrnC+5JOiqRERKTVEGiTU2s3fNbEnkdksz+3v0SxPJx8qV0KkT3HYbnHWWP9escBaRBFOUc9DPA3cBmQCRS6z6RLMokTw5B88+Cy1b+sunRo2CjAw4/PCgKxMRKXVFOQddyTn3qZnlvC8rSvWI5G3NGvjTn2DGDOjaFV58UZdOiUhCK0oLeqOZHQs4ADO7GFgX1apEDnDOt5RbtIBPPvEt6LffVjiLSMIrSgv6OiAdaGpmPwCrgL5RrUoE4L//9UtCTpkC7dvDyJFw7LFBVyUiEhNFGcX9LdDFzCoDhzjndkS/LEl6r74Kf/4z7NwJjz3mV59KSQm6KhGRmCk0oM1sUK7bADjn7otSTZLMNm2C66+HceP8rGCjR/slIkVEkkxRzkH/nOMrGzgHaBDFmiRZTZvmzzVPnOhnBpszR+EsIkmrKF3cj+W8bWaDgSlRq0iSz/btcMstMHw4nHACvPkmnHhi0FWJiASqJOtBVwKOKe1CJEnNmeNDeeRIvwrV/PkKZxERinYO+gsil1gBKUAd/PzcIiXnHDz+ONx5p79k6qOP4JRTgq5KRCQ0inKZVfcc32cBPznnNFGJlNzmzfCHP8DUqXDBBb5ru3r1oKsSEQmVfAPazGpGvs19WdWhZoZzbnP0ypKENXcu9O4N69bBE0/ADTfA/85SJyIiFNyCXojv2s7r09Oh89BSHM7BkCHw179CvXq+S/ukk4KuSkQktPINaOdcw1gWIglsyxbfpT1lCvTs6bu0a9QIuioRkVAryjlozKwG0AiocOA+59zsaBUlCeTTT6FXL/jhB9+CvukmdWmLiBRBUUZxXw3cBNQDFgPtgDnA76NbmsQ15/w55jvugLp1fZf2yScHXZWISNwoynXQNwFtge+dc52BE4ENUa1K4tuWLXDhhX7ykXPOgUWLFM4iIsVUlIDe45zbA2Bm5Z1zy4Em0S1L4tb8+dC6tZ+287HHICMDatYs/OdEROR/FOUc9Fozqw5kADPMbAvwY3TLkrjjHDz1FNx2Gxx5JHz4IbRrF3RVIiJxqyhzcV8Q+fYeM3sfqAZMj2pVEl+2boU//Qlefx3OO89P26lWs4jIQSloopI3gFeADOfczwDOuQ9iVZjEiQUL/CjtNWtg8GC49VaN0hYRKQUFnYNOx0/z+Z2ZjTeznmZWLkZ1Sdg5B08/DaedBllZMHs2DByocBYRKSX5BrRzbrJz7lKgPvA60A9YbWbDzaxrrAqUENq2zbeab7gBunaFzz7TQhciIqWs0FHczrndzrnxkXPRZ+Ivs9I56GS1aJEfpT1pEjzyiJ8drFatoKsSEUk4hQa0mR1uZjeY2cf4kdzvAG2iXpmEz4gRvqW8b5/v0r79djikJEuKi4hIYfL9dDWz/mb2HrAIaAzc4Zw7xjn3V+fc4sKe2MyONrP3zexLM1tqZjeVYt0SS/v3w113wR//CB06+C7tU08NuioRkYRW0GVWpwIPATOdc/tL8NxZwEDn3CIzqwosNLMZzrllJSlUArJ7N1x5JUycCNdc4691Lls26KpERBJeQatZXXUwT+ycWwesi3y/w8y+BI4CFNDx4qef4Pzz/exgjz3mp+7UKG0RkZgo0mpWB8vMGuAHl83L47EBwACA+vXrx6IcKYolS6B7d9iwwU9A0rNn0BWJiCSVgs5BvxkJ1oNiZlWA14CbnXPbcz/unEt3zqU559Lq1KlzsLuT0vD22/765gODwRTOIiIxV9AQ3JHAO2Z2t5mV6KRj5OdeA152zr1ekueQGBs2DLp1g4YN/VrObTRgX0QkCAWdg54Qme5zELDAzMYA+3M8/nhBT2xmBrwIfFnYthIC2dn+sqkhQ3xAjx0LVasGXZWISNIq7CLWTOBnoDxQNddXYU4DrgB+b2aLI1/nHkyxEiU7d/r1m4cMgRtvhMmTFc4iIgEraLGMs4HHgSlAa+fcruI8sXPuI0BDflTWQdEAABLmSURBVMPuhx/8ClSff+4vobr++qArEhERCh7FfTdwiXNuaayKkRhbvNiP1N62DaZOhXPVwSEiEhYFnYM+PZaFSIxNmwZ9+vh1mz/+GFq2DLoiERHJQRMpJxvn4IknoEcPaNoU5s1TOIuIhJACOplkZfklIm++2Qf0Bx/AkUcGXZWIiORBAZ0stm/303b++9/+cqqJE6Fy5aCrEhGRfMRkqk8J2OrVfjDYsmWQng79+wddkYiIFEIBnejmz/eXUe3ZA9OnQ5cuQVckIiJFoC7uRPb669CxI1SsCJ98onAWEYkjCuhE9fjjcNFF0KqVH6ndrFnQFYmISDEooBPRo4/CwIFw8cXw3ntw2GFBVyQiIsWkc9CJ5vHH4Y47/CQkY8ZAGb3EIiLxSC3oRDJ0qG85X3KJwllEJM4poBPFU0/BLbf4884vv6xwFhGJcwroRPDMM36ZyJ49/TrOZcsGXZGIiBwkBXS8e+45uO46P0vY+PEKZxGRBKGAjmfPPw/XXgvdusGECVCuXNAViYhIKVFAx6vhw2HAADjnHHjtNShfPuiKRESkFCmg49GoUXD11XDWWX62MIWziEjCUUDHm5degquu8tN2TpoEFSoEXZGIiESBAjqevPIK9OsHnTtDRoafY1tERBKSAjpejB8PV1wBHTrA1KlQqVLQFYmISBQpoOPBq6/C5ZfDaafBtGkKZxGRJKCADrvXX4dLL4V27eDNN6Fy5aArEhGRGFBAh1lGBvTuDSedBG+9BVWqBF2RiIjEiAI6rKZOhV69oE0bmD4dqlYNuiIREYkhBXQYvfGGX/QiNRXefhsOPTToikREJMYU0GHz1ltw4YXQsiW88w5UqxZ0RSIiEgAFdJi88w5ccAE0b+6/r1496IpERCQgCuiwmDkTevSApk1hxgyoWTPoikREJEAK6DB47z2/XGSjRj6oa9UKuiIREQmYAjpoixfDeefBMcfAu+9C7dpBVyQiIiGggA7Stm1wySX+XPPMmVCnTtAViYhISJQJuoCk5ZxfMnLVKpg1C444IuiKREQkRBTQQXn6aZg4ER55BNq3D7oaEREJGXVxB2HePBg40J97Hjgw6GpERCSEFNCxtnmzn8Kzbl0YORIO0UsgIiK/pS7uWNq/H/r1g3Xr4KOPdK2ziIjkSwEdS4MH+/Wcn3zSr1AlIiKSD/WvxsqHH8Lf/gYXXwzXXx90NSIiEnIK6FhYvx769IGGDeGFF8As6IpERCTk1MUdbdnZcPnlsGmTX0ZSq1OJiEgRKKCj7YEH/Cxh6el+fWcREZEiUBd3NL37LtxzD/Tt62cNExERKSIFdLT8+CNcdplfPvLZZ3XeWUREikVd3NGQlQWXXgo7d8L770OVKkFXJCIicUYBHQ2DBsHs2TBmDDRrFnQ1IiISh9TFXdrefBMefBD69/fnnkVEREpAAV2aVq+GK66AVq3giSeCrkZEROKYArq07NsHvXtDZia8+ipUrBh0RSIiEsd0Drq03HknzJ0LEyZAo0ZBVyMiInFOLejSMGkSDBkCN9wAl1wSdDUiIpIAFNAHa+VKuOoqaNsWHn006GpERCRBKKAPxp490KuXn4RkwgQoXz7oikREJEHoHPTBuPVWWLQIJk+GBg2CrkZERBKIWtAlNXasn8Lz9tvh/PODrkZERBKMArokli/3E5GcdppfrUpERKSUKaCLa9cuP1K7YkUYNw7Klg26IhERSUBRC2gzG25m681sSbT2EYjrr4elS+Hll6FevaCrERGRBBXNFvRI4OwoPn/sjR8PI0bA3/8OZ54ZdDUiIpLAohbQzrnZwOZoPX8g0tOhcWP4v/8LuhIREUlwOgddVJs3wwcfwEUXQUpK0NWIiEiCCzygzWyAmS0wswUbNmwIupz8TZsG2dnQs2fQlYiISBIIPKCdc+nOuTTnXFqdOnWCLid/GRlQty6kpQVdiYiIJIHAAzou7NoF06f71vMh+pWJiEj0RfMyq7HAHKCJma01sz9Fa19RN2MG7N6t7m0REYmZqM3F7Zy7NFrPHXMZGVCtGnTqFHQlIiKSJNRfW5isLJg6Fbp316xhIiISMwrownz0EWzapO5tERGJKQV0YTIy/DrPZyfWpGgiIhJuCuiCOAeTJkHXrlClStDViIhIElFAF2TxYli9Gi64IOhKREQkySigC5KR4a97Pu+8oCsREZEko4AuyKRJcNppEOYZzkREJCEpoPOzciV88YW6t0VEJBAK6PxkZPh/dXmViIgEQAGdn4wMaNUKGjYMuhIREUlCCui8rF8PH3+s1rOIiARGAZ2XKVP8NdAKaBERCYgCOi8ZGdCgge/iFhERCYACOrcdO2DmTN96Ngu6GhERSVIK6NymT4e9e3V5lYiIBEoBnVtGBtSuDaeeGnQlIiKSxBTQOe3bB2+84af2LFMm6GpERCSJKaBzmjULtm1T97aIiAROAZ1TRgZUrgxdugRdiYiIJDkF9AH79/uAPvtsqFgx6GpERCTJKaAPmD8f1q3T5CQiIhIKCugDMjL8wLBu3YKuRERERAH9i0mToFMnqFEj6EpEREQU0AAsXw4rVqh7W0REQkMBDb71DNCjR7B1iIiIRCigwZ9/btsW6tULuhIRERFAAQ0//ACffqrubRERCRUF9OTJ/l/NHiYiIiGigM7IgMaNoWnToCsRERH5RXIH9Nat8P77WvtZRERCJ7kD+o03ICtL3dsiIhI6yR3QGRlw5JFw0klBVyIiIvI/kjegd++Gt97y1z4fkry/BhERCafkTaZ334Wff9blVSIiEkrJG9AZGXDoodC5c9CViIiI/EZyBnR2NkyZ4leuKlcu6GpERER+IzkD+pNPYMMGdW+LiEhoJWdAZ2T4lvM55wRdiYiISJ6SL6Cd86tXdekCVasGXY2IiEieki+gv/gCVq1S97aIiIRa8gX0pEl+Ws/zzw+6EhERkXwlX0BnZMCpp8LhhwddiYiISL6SK6C/+w4WL9bc2yIiEnrJFdAZGf7fHj2CrUNERKQQyRfQLVrAcccFXYmIiEiBkiegN26EDz9U97aIiMSF5AnoqVNh/35dXiUiInEheQI6IwPq14cTTwy6EhERkUIlR0D//DO8845vPZsFXY2IiEihkiOg334b9uxR97aIiMSN5AjojAyoWRNOPz3oSkRERIok8QM6M9MPEDvvPChTJuhqREREiiTxA3r2bNi6Vd3bIiISVxI/oDMyoGJFOPPMoCsREREpssQOaOd8QJ91FlSqFHQ1IiIiRZbYAb1wIaxdq9nDREQk7iR2QE+aBCkp0K1b0JWIiIgUS2IHdEYGdOgAtWoFXYmIiEixRDWgzexsM1thZt+Y2Z3R3NdvfPUVLFum7m0REYlLUQtoM0sB/g2cAzQDLjWzZtHa329o7WcREYlj0WxBnwR845z71jm3DxgHxC4tMzKgTRu/QIaIiEiciebUWkcBa3LcXgucnHsjMxsADACoX1phmp0Nxx7rA1pERCQORTOg81o2yv3mDufSgXSAtLS03zxeIikpMGZMqTyViIhIEKLZxb0WODrH7XrAj1Hcn4iISMKIZkDPBxqZWUMzKwf0AaZEcX8iIiIJI2pd3M65LDO7HngbSAGGO+eWRmt/IiIiiSSq6y86594E3ozmPkRERBJRYs8kJiIiEqcU0CIiIiGkgBYREQkhBbSIiEgIKaBFRERCSAEtIiISQgpoERGREFJAi4iIhJACWkREJITMudJZQKo0mNkG4PtSfMrawMZSfL4gJcqxJMpxgI4lrBLlWBLlOEDHUpDfOefq5PVAqAK6tJnZAudcWtB1lIZEOZZEOQ7QsYRVohxLohwH6FhKSl3cIiIiIaSAFhERCaFED+j0oAsoRYlyLIlyHKBjCatEOZZEOQ7QsZRIQp+DFhERiVeJ3oIWERGJSwkR0GZ2tpmtMLNvzOzOPB4vb2bjI4/PM7MGsa+yYGZ2tJm9b2ZfmtlSM7spj206mdk2M1sc+RoURK1FYWbfmdkXkToX5PG4mdmTkdfkP2bWOog6C2NmTXL8vheb2XYzuznXNqF9XcxsuJmtN7MlOe6raWYzzOzryL818vnZfpFtvjazfrGrOs9a8jqOR81seeTvZ5KZVc/nZwv8W4y1fI7lHjP7Icff0Ln5/GyBn3Wxls+xjM9xHN+Z2eJ8fjY0r0t+n7+Bv1ecc3H9BaQAK4FjgHLA50CzXNv8BRgW+b4PMD7ouvM4jiOB1pHvqwJf5XEcnYBpQddaxOP5DqhdwOPnAm8BBrQD5gVdcxGOKQX4L/66xbh4XYAOQGtgSY77HgHujHx/J/BwHj9XE/g28m+NyPc1QnYcZwJlIt8/nNdxRB4r8G8xJMdyD3BbIT9X6GddGI4l1+OPAYPC/rrk9/kb9HslEVrQJwHfOOe+dc7tA8YBPXJt0wMYFfl+InCGmVkMayyUc26dc25R5PsdwJfAUcFWFVU9gNHOmwtUN7Mjgy6qEGcAK51zpTmZTlQ552YDm3PdnfP9MAromcePngXMcM5tds5tAWYAZ0et0ELkdRzOuXecc1mRm3OBejEvrATyeU2KoiifdTFV0LFEPmN7AWNjWlQJFPD5G+h7JREC+ihgTY7ba/ltsP2yTeQNvQ2oFZPqSiDSBX8iMC+Ph08xs8/N7C0zax7TworHAe+Y2UIzG5DH40V53cKmD/l/2MTL6wJwuHNuHfgPJuCwPLaJt9fnj/gembwU9rcYFtdHuuuH59OVGm+vyenAT865r/N5PJSvS67P30DfK4kQ0Hm1hHMPTS/KNqFgZlWA14CbnXPbcz28CN+92gp4CsiIdX3FcJpzrjVwDnCdmXXI9XjcvCYAZlYOOB94NY+H4+l1Kaq4eX3M7G4gC3g5n00K+1sMg2eBY4FUYB2+azi3uHlNIi6l4NZz6F6XQj5/8/2xPO4rldclEQJ6LXB0jtv1gB/z28bMygDVKFkXU1SZWVn8H8fLzrnXcz/unNvunNsZ+f5NoKyZ1Y5xmUXinPsx8u96YBK+ey6norxuYXIOsMg591PuB+LpdYn46cDphMi/6/PYJi5en8iAnO7A5S5yQjC3IvwtBs4595NzLts5tx94nrxrjIvXBH75nL0QGJ/fNmF7XfL5/A30vZIIAT0faGRmDSOtnD7AlFzbTAEOjKy7GHgvvzdzUCLna14EvnTOPZ7PNkccOHduZifhX79NsauyaMyssplVPfA9fjDPklybTQGuNK8dsO1AV1JI5dsaiJfXJYec74d+wOQ8tnkbONPMakS6W8+M3BcaZnY28FfgfOfcrny2KcrfYuByjb+4gLxrLMpnXVh0AZY759bm9WDYXpcCPn+Dfa8EPXquNL7wI4K/wo9wvDty3334Ny5ABXzX5DfAp8AxQdecxzG0x3eL/AdYHPk6F7gWuDayzfXAUvzozbnAqUHXnc+xHBOp8fNIvQdek5zHYsC/I6/ZF0Ba0HUXcDyV8IFbLcd9cfG64P9TsQ7IxP9P/0/48RfvAl9H/q0Z2TYNeCHHz/4x8p75BrgqhMfxDf7c34H3y4ErNeoCbxb0txjCYxkTeR/8Bx8KR+Y+lsjt33zWhe1YIvePPPD+yLFtaF+XAj5/A32vaCYxERGREEqELm4REZGEo4AWEREJIQW0iIhICCmgRUREQkgBLSIiEkIKaJE4Ell1Z5WZ1YzcrhG5/btc280ys7Ny3XezmT1TyPPvLP2qRaQkFNAiccQ5twY/LeRDkbseAtLdbxfwGIufyCKnguYSF5GQUUCLxJ8hQDvz61K3J+95mycC3c2sPPyyAEBd4CMzq2Jm75rZosh6vL9ZEcn8GtfTctx+2sz+EPm+jZl9EFnk4O0cUyHeaGbLIgs+jCvdQxZJPmWCLkBEisc5l2lmtwPTgTOdX3ow9zabzOxT/LJ3k/l1HXRnZnuAC5xz2yNzhs81symuCLMWReYrfgro4ZzbYGa9gQfwMyndCTR0zu01s+qldbwiyUotaJH4dA5+isUWBWyTs5s7Z/e2Af8ys/8AM/FL4x1exP02iexzhpktBv7Or+sw/wd42cz64leXEpGDoBa0SJwxs1SgK9AO32U9zuW90EgG8LiZtQYqusiC9MDlQB2gTaQ1/h1+vvqcsvjf/8AfeNyApc65U/LYXzegA35Zzn+YWXPn118XkRJQC1okjkRW3XkWv17tauBRYHBe2zq/BOYsYDj/OzisGrA+Es6dgd/l8ePfA83MrLyZVQPOiNy/AqhjZqdE6ilrZs3N7BDgaOfc+8AdQHWgysEdrUhyU0CLxJf+wGrn3IzI7WeApmbWMZ/txwKtgJyDtl4G0sxsAb41vTz3D0VGi08g0m0NfBa5fx9+ydaHzexz/Ko/pwIpwEtm9kVk2yHOua0Hc6AiyU6rWYmIiISQWtAiIiIhpIAWEREJIQW0iIhICCmgRUREQkgBLSIiEkIKaBERkRBSQIuIiISQAlpERCSE/h8NUfDfJ7sEMQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import numpy as np  \n",
    "import math  \n",
    "  \n",
    "  \n",
    "x_vals = np.linspace(0, 20, 20)  \n",
    "y_vals = [math.sqrt(i) for i in x_vals]  \n",
    "plt.xlabel('X Values')  \n",
    "plt.ylabel('Y Values')  \n",
    "plt.title('Square Roots')  \n",
    "plt.plot(x_vals, y_vals, 'r', label = 'Square Root')  \n",
    "plt.legend(loc='upper center')  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x15a70241088>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import numpy as np  \n",
    "import math  \n",
    " \n",
    "\n",
    "x_vals = np.linspace(0, 20, 20)  \n",
    "y_vals = [math.sqrt(i) for i in x_vals]  \n",
    "y2_vals = x_vals ** 3  \n",
    "plt.xlabel('X Values')  \n",
    "plt.ylabel('Y Values')  \n",
    "plt.title('Square Roots')  \n",
    "plt.plot(x_vals, y_vals, 'r', label = 'Square Root')  \n",
    "plt.plot(x_vals, y2_vals, 'b', label = 'Cube')  \n",
    "plt.legend(loc='upper center')  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2.3. Plotting using CSV and TSV Files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd  \n",
    "data = pd.read_csv(\"E:\\Hands on Python for Data Science and Machine Learning\\Datasets\\iris_data.csv\")  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   sepal_length  sepal_width  petal_length  petal_width species\n",
       "0           5.1          3.5           1.4          0.2  setosa\n",
       "1           4.9          3.0           1.4          0.2  setosa\n",
       "2           4.7          3.2           1.3          0.2  setosa\n",
       "3           4.6          3.1           1.5          0.2  setosa\n",
       "4           5.0          3.6           1.4          0.2  setosa"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x15a720edec8>]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import numpy as np  \n",
    "import math  \n",
    "  \n",
    "plt.xlabel('Sepal Length')  \n",
    "plt.ylabel('Petal Length')  \n",
    "plt.title('Sepal vs Petal Length')  \n",
    "plt.plot(data[\"sepal_length\"], data[\"petal_length\"], 'b')  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SepalLength</th>\n",
       "      <th>SepalWidth</th>\n",
       "      <th>PetalLength</th>\n",
       "      <th>PetalWidth</th>\n",
       "      <th>TrainingClass</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SepalLength  SepalWidth  PetalLength  PetalWidth TrainingClass\n",
       "0          5.1         3.5          1.4         0.2   Iris-setosa\n",
       "1          4.9         3.0          1.4         0.2   Iris-setosa\n",
       "2          4.7         3.2          1.3         0.2   Iris-setosa\n",
       "3          4.6         3.1          1.5         0.2   Iris-setosa\n",
       "4          5.0         3.6          1.4         0.2   Iris-setosa"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd  \n",
    "data = pd.read_csv(\"E:\\Hands on Python for Data Science and Machine Learning\\Datasets\\iris_data.tsv\", sep='\\t')  \n",
    "data.head()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x15a721657c8>]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import numpy as np  \n",
    "import math  \n",
    " \n",
    "plt.xlabel('Sepal Length')  \n",
    "plt.ylabel('Petal Length')  \n",
    "plt.title('Sepal vs Petal Length')  \n",
    "plt.plot(data[\"SepalLength\"], data[\"PetalLength\"], \"b\")  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2.4. Scatter Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x15a721cdf48>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAegAAAGDCAYAAADgY4OVAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nO3de5xkZX3n8e93qnuUQS4qY1QuMyKKKy4iTFAWJehMNpIgiQmJmHETiWbMTIya66qzL2MuHeOaZMFESDqayDoDXogmxlWjosQIEdODyEUwMcgAotLcxfHCzPz2j3OKqa6pqq5TXU/Vc6o/79erXt116vSp3zmH4dfn1LefxxEhAACQlxXjLgAAAOyPBg0AQIZo0AAAZIgGDQBAhmjQAABkiAYNAECGaNDAGNm+xfaGcdcxDLbfbHvbuOvoxfbptm8fdx1AP2jQgCTbz7V9pe37bd9j+wrbPzzuupaqbEh7bT9o+9u2v2L73D5/9nLbrxxiHSNvjLbD9jGjfl9gGKbGXQAwbrYPlvQRSZslvV/SSknPk/T9cdY1RHdExBG2LeknJV1q+6qI+PK4CwPQHVfQgPRUSYqISyJiT0R8NyI+ERHXNlew/Uu2b7R9r+1/sr2m5bWw/RrbN9u+y/bbbK8oX3uy7U/bvrt8bbvtQxcryPZzbH/TdqNl2YttX1t+f7LtOdsP2P6W7T9bbJtR+HtJ90p6esv7XGn7Pttfsn16uXxGxS8pf1Feff9Fufx827eV77vD9vP6OL6L7esjbP+J7VvLfflL2weUr51u+3bbv2n7TtvfaL0DYPuxtv+xrOffbP+h7c+Vr322XO1L5T68pOXnOm4PyAkNGpD+XdIe2xfZPsP2o1tftP1Tkt4o6aclrZb0L5IuadvGiyWtk3SiiqvUX2r+uKS3SHqipP8i6UhJb16soIj4vKTvSHpBy+Kfl3Rx+f35ks6PiIMlPVnFlX9PtlfYfrGkQyVdZ/twSf9P0h9Keoyk35L0d7ZXR8TWcj9fHRGPiohXl5v5N0knlOtfLOkDth+52Hsv4q0qfkk6QdIxkg6X9KaW1x8v6ZBy+SskvaPlHL1DxXF6vKRfLB+SpIg4rfz2meU+vK+P7QHZoEFj2YuIByQ9V1JI+mtJ87Y/bPuHylVeJektEXFjROyW9EeSTmi9ipb01oi4JyJulXSepJeW2/5qRHwyIr4fEfOS/kzSj/RZ2iXN7dg+SNKPa98vBg9JOsb2YRHxYNnQu3mi7fsk3SXpdyX9j4j4iqSXSfpoRHw0IvZGxCclzZXv01FEbIuIuyNid0T8qaRHSDq2z/3ZT3nb/Zcl/Xp5/L6t4vie07LaQ5J+PyIeioiPSnpQ0rHl3YWfkfS7EbGrvGV/UR9v23F7g+4DkAoNGpBUNt+XR8QRkp6h4or3vPLlNZLOL28D3yfpHhVXxoe3bOK2lu93lj8v24+z/V7bX7f9gKRtkg7rs6yLJf207UeouHq/OiJ2lq+9QsVV503lrd0ze2znjog4NCIeExEnRMR7W/brZ5v7Ve7bcyU9oduGylvDN5ZhuvtUXIn2uz+drJa0StKOlho+Xi5vurv8xahpl6RHletMaeGxb/2+m27bA7JCgwbaRMRNkt6tolFLxf/0X1U2uebjgIi4suXHjmz5/ihJd5Tfv0XFlfnx5e3ol6lo7v3U8WUVzf4MLby9rYj4j4h4qaTHqbhFfKntA6vtqW6T9J62/TowIv64+TatK5efN/9PST8n6dERcaik+/vdny7ukvRdSce11HBIRPTTMOcl7ZZ0RMuyI7usC9QODRrLnu2nlVeGR5TPj1Rxa7l52/gvJb3B9nHl64fY/tm2zfy27UeXP/taSc3POw9ScQv1vvIz39+uWN7Fkl4j6TRJH2ip+WXlZ8V7Jd1XLt5TcdvbJL3I9o/Zbth+ZBnKaja8b0k6umX9g1Q0xHlJU7bfJOngKm9YvsfDD+37WOH/2H5cuc7htn9ssW1FxB5JH5T0ZturbD9N0i+0rda+D0Bt0KAB6duSni3pKtvfUdGYr5f0m5IUER9ScZX63vI29fUqrmpb/YOkHZKuURG8ele5/PdUBMfuL5d/sGJtl0g6XdKnI+KuluUvlHSD7QdVBMbOiYjvVdlwRNymItD2RhVN9zYVv0A0/79wvqSzXSTX3y7pnyR9TEWobqek76m/W8pNh6u4Wm59PFnFVflXJX2+PL6fUv+fCb9axW32b0p6j4rj1frncW+WdFF5+/znKtQKjJ0jYvG1AHRlOyQ9JSK+Ou5aljvbb5X0+Ij4xUVXBjLHFTSA2io/njjehZNVhOc+NO66gGFgJDEAdXaQitvaT5R0p6Q/VfFxA1B73OIGACBD3OIGACBDNGgAADKU1WfQhx12WKxdu3bcZQAAMBI7duy4KyJWd3otqwa9du1azc3NjbsMAABGwvbObq9xixsAgAzRoAEAyBANGgCADNGgAQDIULIGbftY29e0PB6w/bpU7wcAwCRJluKOiK9IOkGSbDckfV2MkQsAQF9GdYt7vaT/jIiucXIAALDPqBr0OSoGtAcAAH1I3qBtr5R0lqQPdHl9k+0523Pz8/OpywEAoBZGcQV9hqSrI+JbnV6MiNmIWBcR61av7jjaGQAAy84oGvRLxe1tAEBC27dLa9dKK1YUX7dvH3dFS5d0LG7bqyT9qKRXpXwfAMDytX27tGmTtGtX8XznzuK5JG3cOL66lirpFXRE7IqIx0bE/SnfBwCwfG3duq85N+3aVSyvM0YSAwDU2q23VlteFzRoAECtHXVUteV1QYMGANTazIy0atXCZatWFcvrjAYNAKi1jRul2VlpzRrJLr7OztY7ICYlTnEDADAKGzfWvyG34woaAIAM0aABAMgQDRoAUHtbtkhTU8Vn0FNTxfO64zNoAECtbdkiXXjhvud79ux7fsEF46lpGLiCBgDU2uxsteV1QYMGANTanj3VltcFDRoAUGuNRrXldUGDBgBkqd8pJJszV/W7vC4IiQEAslNlCslmEGx2trit3WgU69Y5ICZJjohx1/CwdevWxdzc3LjLAACM2dq1RVNut2aNdMsto64mHds7ImJdp9e4xQ0AyM6kTiFZBQ0aAJCdSZ1CsgoaNAAgO5M6hWQVNGgAQHYmdQrJKkhxAwCyNIlTSFbBFTQAABmiQQMAkCEaNAAAPfQ7otmw8Rk0AABdVBnRbNi4ggYAoIutW/c156Zdu4rlqdGgAQDoYpwjmtGgAQDoYpwjmtGgAQD7GVcwKjfjHNGMBg0AWKAZjNq5U4rYF4xajk16nCOaMd0kAGCB5TLVYw6YbhIA0DemeswDDRoAsABTPeaBBg0AWICpHvNAgwYALMBUj3lgqE8AwH6W+1SPOeAKGgCADNGgAQDIEA0aAJaBlCOD5TDqWA41DBufQQPAhEs5ZeI4p2PMqYYUGEkMACZcypHBchh1LIcaBsVIYgCwjKUcGSyHUcdyqCEFGjQATLiUI4PlMOpYDjWkkLRB2z7U9qW2b7J9o+1TUr4fgDxMYmCnzmZmpOnphcump4czMlgOo47lUEMKqa+gz5f08Yh4mqRnSrox8fsBGDOmKsyT3fv5oHIYdSyHGlJIFhKzfbCkL0k6Ovp8E0JiQP3VObAzqTgn+RpXSOxoSfOS/tb2F22/0/aBHYrbZHvO9tz8/HzCcgCMwqQGduqMc1JPKRv0lKQTJV0YEc+S9B1Jr29fKSJmI2JdRKxbvXp1wnIAjMKkBnbqjHNSTykb9O2Sbo+Iq8rnl6po2AAm2KQGdlrlEoLrt47lcE4mUbIGHRHflHSb7WPLReslfTnV+wHIw6QGdppyCcFVqWPSz8mkSjqSmO0TJL1T0kpJN0s6NyLu7bY+ITEAucslcJVLHViaXiGxpGNxR8Q1kjq+MQDUUS6Bq1zqQDqMJAYAFeQSuMqlDqRDgwZQK6kCWnULXFWtI5dgGyqIiGweJ510UgBAN9u2RaxaFVHEoorHqlXF8lFud9u2iDVrIuzi61Lff1D91pHquGHpJM1Fl57IdJMAaiNVMGrSA1eTvn91xnSTACZCqmDUpAeuJn3/JhUNGkBtpApGTXrgatL3b1LRoAHURqqA1sxMEZ5qtWLF8IJf4w5o5RJsQzU0aAC1kWpErCuukPbuXbhs795i+VLlMPIYI4nVEyExAMve1JS0Z8/+yxsNaffupW2bgBZ6ISQGAD10as69lldBQAuDokEDWPYajWrLqyCghUHRoIFlLFV4acuW4raxXXzdsmU466ayaVO15VUQ0MKgaNDAMpUqvLRli3ThhftuD+/ZUzzv1HirrJvSqafuf7XcaBTLl4qAFgZFSAxYplKFl6oErlKGs6ogyIVxISQGYD+pwktVAlcpw1lVEORCjmjQwDKVKrxUJXCVMpxVBUEu5IgGDSxTqcJLVQJXg4SzUgTbmLoRWeo2zdU4Hkw3CYxWqmkTN2+OaDSKaQ0bjeJ5t/efmlo4DeLU1HimTWTqRoyDmG4SQI6qhrNyCHPlUAMmByExAFmqGs7KIcyVQw1YHmjQAMamajgrhzBXDjVgeaBBA+hLDuGsHEblGqQGQmUYSLcPp8fxICQG5CmHcNag66dQpQZCZehFhMQALAXBqMFx7NALITEAS0IwanAcOwyKBg1gUQSjBsexw6Bo0AAWlTKclcN0kynlEGxDPdGgASwq1ZSJuUw3mRLTTWJQhMQAjE0u000C40JIDECWcpluEsgRDRrA2OQy3SSQIxo0gLHJZbrJlNsFBjU17gIALF8XXFB8nZ0tbms3GkVzbi5vt3178fquXcXznTv3NfOlhK5SbRdYCkJiAGoj1ahcjPaFcSEkBmAipBqVi9G+kCMaNIDaSDUqF6N9IUc0aGAMNmwoBq1oPjZs6L5u1fBSDmGnVDXMzEgrVy5ctnLl0kflSj3aVw7nBDXUbZqrcTyYbhLLwfr1C6cebD7Wr99/3apTFeYwtWHqqSmnpxdue3p6PNNeVtnuuM8J8iWmmwTyYXd/rf2fY9XwUg5hp5Q15LB/VdWxZoxOr5AYDRoYsSoNesWK/Zc1t7F37/7Lq66fQsoacti/qupYM0aHFDdQU1XDSzmEnVLWkMP+VVXHmpGHpA3a9i22r7N9jW0ujTHR+g0CrV/f//Kq4aWZGWl6euGy6enRTm2YsoaUYa6UwTamm8QgRnEF/fyIOKHbJTwwCZojUe3cWdzObI5E1el/8p/61P7NeP36Ynm7QaYqbL+F3uuWeiqpakg1dWOV85dLzZh8ST+Dtn2LpHURcVc/6/MZNOoqlyBQDnXkUENVdawZk2FsITHbX5N0r6SQ9FcRMdthnU2SNknSUUcdddLOTv9KgMzlEgTKoY4caqiqjjVjMowzJHZqRJwo6QxJv2r7tPYVImI2ItZFxLrVq1cnLgdII5cgUA515FBDVXWsGZMvaYOOiDvKr3dK+pCkk1O+HzBs/QaHcgkCVa0jRTBqZkaaapsnb2oq71AUI4khS91GMFnqQ9KBkg5q+f5KSS/s9TOMJIacDDKKV4qRqKrqt45UI1xt3tx5pLTNm5e23dQYSQzjoHGMJGb7aBVXzVIx7/TFEdHz91FCYsjJpAeHUu3f1FQxt3O7RkPavXvw7dbVpP93hKXp9Rn0VKeFwxARN0t6ZqrtA6lN+hSEqfavU3PutXzSTfp/R0iHkcSALiY9OJRq/xqNassn3aT/d4R0aNBAF7kEv1JNN5kqULZpU7XldVTlnOTy3xFqqNuH0+N4EBJDbsYd/Eo93WSqQNnmzRGNRrFeo5F/QKyKQUJf4/7vCPkS000C9ZTLdJMEnfbhWGCYmG4SqKlcpptkpK19OBYYJqabBGoql+kmCTrtw7HAqNCggYwNMt1klfW3bCn+btkuvm7ZMpzt1nHkrFxGjavjsUMi3T6cHseDkBiwv6oBo37Xrzri17hHKEspl1Hj6njssDQiJAagXaoRv+oYosql5lzqwOjwGTSA/aQa8auOI2flUnMudSAPNGhgmUo14lcdQ1S51JxLHcgDDRpYplKN+JVTiCqX4Fe/cqkDmej24fQ4HoTEgNHZti1iamphIGlqajiBpBxCVLkEv6rKpQ6MhgiJAWhXx0BSlZrruH9YfgiJAdhPHQNJVWqu4/4BrWjQwDJVx0BSlZrruH9AKxr0MjDpIxOl3L8UgaTU6jY6WKqpGwlcofa6fTg9jgchseGb9JGJUu5fykBSKnUbHSz11I0ErpA7LSUkZvtUSW+WtEbSlCQXfT2OHvYvC4TEhm/SgzIp96+OgaS6jQ6Wy3EDxmVJ003avknSr0vaIenhf/oRcfcwi5Ro0ClM+tR4KfevyrZzOc5299eW8gcbTGMJpLHUFPf9EfGxiLgzIu5uPoZcIxKZ9KBMyv2rYyCpbqOD5XLcgBx1bdC2T7R9oqTP2H6b7VOay8rlqIFJD8qkDDrVMZCUy+hguYzgVceQH/Cwbh9OS/pMj8enu/3cUh6ExNKY9KBMyqBTHQNJmzdHNBrF/jUa3QNiVaU6znUcdQwYFi0xJHZ0RNy82LJh4DNopEQgaTRyOc51DPlh+VnqZ9CXdlj2gaWVBIweI0uNRi7HmVHHUHdT3V6w/TRJx0k6xPZPt7x0sKRHpi4MGLajjup8lUQgabhyOc5V6silZqBVryvoYyWdKelQSS9qeZwo6ZfTlwYMVy5BrrpKFfxKFc6qY8gPWKDbh9PNh6RTFltnWA9CYkgtlyBX3aQKfqUOZ9Ux5IflRUsMif25pPaV7i83+g/D/GWBkBiQJ0YSA9JYakjsEZJOkPQf5eN4SY+R9Arb5w2tSgDZShWiIpwFdNc1JNbiGEkviIjdkmT7QkmfkPSjkq5LWBuATKQKURHOArrr5wr6cEkHtjw/UNITI2KPpO8nqQrIRJUAU7/TPKasIZVUISrCWUAP3T6cbj4kvULS1yT9raR3S7pZ0itVNOq3LfbzVR6ExJCTKgGmqtM8pqghtZQjfhHOwnKlpYTEJMn2EySdrGKqyS9ExB0pflkgJIacVAkw1W2aRwB5WGpIrLnevKR7JB1j+7RhFQfkqkqAqVNz7rU8RQ0AJsuiITHbb5X0Ekk3SGrO0BqSPpuwLmDsqgSYGo3uV9CjqgHAZOnnCvqnJB0bET8RES8qH2elLgwYt5kZaeXKhctWruwcYKo6zWMu0zECyFc/DfpmSdOpCwFy1B7R6BbZOPXU4nPoVlNTxfJ227cXjXvnzmJ7O3cWzzs16Y0bpdnZ4jNnu/g6O1ssBzDZ+hlJ7O8kPVPSZWr5s6qIeM2wiyEkhpykmq6Q4BeApl4hsX4GKvlw+QCWlVTTFRL8AtCPRRt0RFxk+wBJR0XEV0ZQE5CFVNMVEvwC0I9FP4O2/SJJ10j6ePn8BNt9X1Hbbtj+ou2PDF4mMBxVRvtKNV3hzIw03ZbqmJ4eXvCryshjOYxSBqCzfkJib1YxSMl9khQR10h6UoX3eK2kGytXBgzZli3ShRfu+3OoPXuK592adJWAVtUwl937+aCqBNCqrAtg9PoJiV0VEc+2/cWIeFa57NqIOH7RjdtHSLpI0oyk34iIM3utT0gMKaUa7auqlCExwmpAvSx1JLHrbf+8pIbtp5TzQ1/Z53ufJ+l3tG+Ak07FbbI9Z3tufn6+z80C1aUa7auqlCExwmrA5OinQf+apONU/InVxZLuV3HbuifbZ0q6MyJ29FovImYjYl1ErFu9enUf5QCD6Taq11JH+6qqWxhsGCGxKttOWQeApVu0QUfErojYGhE/XD7+l4pb1os5VdJZtm+R9F5JL7C9bWnlos7GHUiqOtqXlKbmKiOUDbLtFME2AGPQbZqrXg9Jt1Zc/3RJH1lsPaabnFy5TJu4eXNEo1G8f6PRezrIVDVv2xYxPb1wu9PT45m+kakegfHSUqebbGf7tog4ssL6p0v6rSAktmzVMZCUquY6HgsAaQw0kpjtx3R7qXz0LSIul3R5lZ/BZKljIClVzXU8FgBGr9dIYjtUTCvZqRn/IE05mFR1HD0rVc11PBYARq9rSCwinhQRR5df2x9Hj7JI1F8ugaQqoa9UNedyLADkrZ8/swKWLIdpE6uOnJWq5hyOBYD8DRQSS4WQGFIinAUgN0sdSQyYCISzANTJICluSVJE3DP8coB0CGcBqJNBU9whiaAYamVmRjr3XOmhh/YtG+Y0jwAwTF0bdERUmVISqIVU0zwCwLD19Rm07UfbPtn2ac1H6sKAYdu6VfpB21/w/+AHxXIAyE2vW9ySJNuvVDF71RGSrpH0HEn/KukFaUsDhouQGIA66ecK+rWSfljSzoh4vqRnSWLiZtQO0ysCqJN+GvT3IuJ7kmT7ERFxk6Rj05YFDN8gI3iNe4pMAMvXore4Jd1u+1BJfy/pk7bvlXRH2rKA4WuO1LV1a3Fb+6ijiubcbQSv5shju3YVz5sjj7VuCwBSqTSSmO0fkXSIpI9FxEOLrV8VI4khJ4w8BiC1JY0kZvs9ze8j4p8j4sOS/maI9QFZIlQGYJz6+Qz6uNYnthuSTkpTDpAPQmUAxqlrg7b9BtvflnS87Qdsf7t8fqekfxhZhRgpQlH7VA2VcewADFOv+aDfEhEHSXpbRBwcEQeVj8dGxBtGWCNGpOp0jJOuyrSQHDsAw7ZoSMz2Ckk/L+lJEfEHto+U9ISI+MKwiyEkNl6EogbHsQMwiKVON/kOSaeoaNKS9GC5DBOGUNTgOHYAhq2fBv3siPhVSd+TpIi4V9LKpFVhLAhFDY5jB2DY+mnQD5XJ7ZAk26sl7U1aFcZikJG2UODYARi2fhr02yV9SNLjbM9I+pykP0paFcaiSigKC3HsAAxbXyOJ2X6apPWSLOmyiLgxRTGExAAAy0mvkFjXsbhtP1LSr0g6RtJ1kv4qInanKREAALTqdYv7IknrVDTnMyT9yUgqAgAAPRv00yPiZRHxV5LOlnTaiGrCkFUZ4YrRsAAgD72mm3x4tqqI2G17BOVg2KpMmcj0igCQj64hMdt7JH2n+VTSAZJ2ld9HRBw87GIIiQ1flRGuGA0LAEZroJBYRDTSlYRRqTLCFaNhAUA++vk7aNRYlRGuGA0LAPJBg55wVUa4YjQsAMgHDXrCVRnhitGwACAffY0kNiqExAAAy8lSp5sEAAAjRoMGACBDNGgAADJEgwYAIEM0aAAAMkSDBgAgQzRoAAAylKxB236k7S/Y/pLtG2z/Xqr3wngwNSUApNNrusml+r6kF0TEg7anJX3O9sci4vMJ3xMjwtSUAJBWsivoKDxYPp0uH/kMW4Yl2bp1X3Nu2rWrWA4AWLqkn0Hbbti+RtKdkj4ZEVd1WGeT7Tnbc/Pz8ynLwRAxNSUApJW0QUfEnog4QdIRkk62/YwO68xGxLqIWLd69eqU5WCImJoSANIaSYo7Iu6TdLmkF47i/ZAeU1MCQFopU9yrbR9afn+ApA2Sbkr1fhgtpqYEgLRSprifIOki2w0Vvwi8PyI+kvD9MGIbN9KQASCVZA06Iq6V9KxU2wcAYJIxkhgAABmiQQMAkCEaNAAAGaJBAwCQIRo0AAAZokEDAJAhGjQAABmiQQMAkCEaNAAAGaJBAwCQIRo0AAAZokEDAJAhGjQAABmiQQMAkCEaNAAAGaJBAwCQIRo0AAAZokEDAJAhGjQAABmiQQMAkCEaNAAAGaJBAwCQIRo0AAAZokEDAJAhGjQAABmiQQMAkCEaNAAAGaJBAwCQIRo0AAAZokEDAJAhGjQAABmiQQMAkCEaNAAAGaJBAwCQIRo0AAAZokEDAJAhGjQAABmiQQMAkCEaNAAAGaJBAwCQIRo0AAAZStagbR9p+zO2b7R9g+3XpnovAAAmzVTCbe+W9JsRcbXtgyTtsP3JiPhywvcEAGAiJLuCjohvRMTV5ffflnSjpMNTvR8AAJNkJJ9B214r6VmSrurw2ibbc7bn5ufnR1EOAADZS96gbT9K0t9Jel1EPND+ekTMRsS6iFi3evXq1OUAAFALSRu07WkVzXl7RHww5XstN9u3S2vXSitWFF+3b1+eNQDApEoWErNtSe+SdGNE/Fmq91mOtm+XNm2Sdu0qnu/cWTyXpI0bl08NADDJHBFpNmw/V9K/SLpO0t5y8Rsj4qPdfmbdunUxNzeXpJ5JsnZt0RDbrVkj3XLL8qkBAOrO9o6IWNfptWRX0BHxOUlOtf3l7NZbqy2f1BoAYJIxklgNHXVUteWTWgMATDIadA3NzEirVi1ctmpVsXw51QAAk4wGXUMbN0qzs8XnvXbxdXZ2tOGsHGoAgEmWLCQ2CEJiAIDlpFdIjCtoAAAyRIMGACBDNGgMLJeRxLZskaamis/Cp6aK5+OQy/EAMBlSTjeJCZbLSGJbtkgXXrjv+Z49+55fcMHo6sjleACYHITEMJBcRhKbmiqacrtGQ9q9e3R15HI8ANQLITEMXS4jiXVqzr2Wp5LL8QAwOWjQGEguI4k1GtWWp5LL8QAwOWjQGakSMkoVjNqwodhm87FhQ+f1Zmak6emFy6anRz+SWPNz3n6Xp8LIagCGjQadiWbIaOdOKWJfyKhTk24Go5q3cZvBqKU26Q0bpMsuW7jsssu6N2m79/NRuOACafPmfVfMjUbxfJQBMYmR1QAMHyGxTFQJGaUKRvVqsO3/mRCKAoClIyRWA1VCRjkEowhFAUBaNOhMVAkZ5RCMIhQFAGnRoBOqEvqqEjKqGozqN/i1fn3/y2dmiv1qtWJF71BUlWBbDoG5qhhJDMBQRUQ2j5NOOikmxbZtEatWRRSf3haPVauK5b1+Zs2aCLv42mvdzZsjGo1iu41G8byT9esX1tB8rF/f+f07rdupjirbbdbbaf1OdVc5dlW2m9Ig5xsAJM1Fl55ISCyRXEJUqYJfVbYrVQu25RCYqyqX8w2gXnqFxGjQiaxY0blR2dLevaOro0ojrVJz1QadSx2p5HK+AdQLKe4xqGOIKmXNVYJtdQvMSfU83wDyRoNWmnDPICGqKvoNRlUNfrU3tkajc81VtitVC7alDMylCnIxkhiAYVv2DbrKCF5VXHHF/rc29+4tli9VlZHEzj238zY6Lb/iiv0/z92zp3PNT31q5+12W37qqZ2b/6mn7jHs3QYAAAo1SURBVL9ulVG5qowklupcV60ZAPqx7D+DThXuSRleyiFwVXX/cghR5VADALQiJNZDqnBPyvBSDoGrqvuXQ4gqhxoAoBUhsR5ShXtShpdyCFxV3b8cQlQ51AAA/Vr2DbpqmKvfkNEg0yCm2HaqwFXV/UsZour3uOUyRSYA9KXbCCbjeIxjJLFUI1w1t93PaF+j2HY/I5Rt27Zvm81HozGcGqrUUUWV47ZtW8TKlQvXXbmS0b4AjI8YSay7VIGrqnIIMOVQQ1VVaq7j/gGYbITEekgVuKoqhwBTDjVUVaXmOu4fgMlGSKyHVIGrqnIIMOVQQ1VVaq7j/gFYvpZ9g04VuKoqh5GoZmaklSsXLlu5Mu8QVZXjlsMxbmJqSgCL6vbh9Dge45puMkXgahApt93v+09PLwxRTU/nH6KqctzGfYybNTA1JYAIQmLoEyGq0eA4A2jiM2j05dZbqy3HYDjOAPpBg8bDCFGNBscZQD9o0HhYTiGqScZxBtCPiW3QpGSrY8rE0eA4A+jHRIbEmvP+7tq1b9mqVfxPEACQl2UXEtu6dWFzlornW7eOpx4AAKqayAZNShYAUHfJGrTtv7F9p+3rU71HN6RkAQB1l/IK+t2SXphw+13lkpIlqAYAGFSyBh0Rn5V0T6rt95JDSrYZVNu5sxjMcefO4jlNGgDQj6QpbttrJX0kIp7Rz/qTNNQnwzkCABaTdYrb9ibbc7bn5ufnx13O0BBUAwAsxdgbdETMRsS6iFi3evXqcZczNATVAABLMfYGPalyCaoBAOop5Z9ZXSLpXyUda/t2269I9V45yiGoBgCor4kc6hMAgDrIOiQGAAD2R4MGACBDNGgAADJEgwYAIEM0aAAAMkSDBgAgQzRoAAAyRIMGACBDNGgAADJEgwYAIENZDfVpe15Sh1mUs3SYpLvGXURC7F/9Tfo+sn/1xv4V1kREx6kcs2rQdWJ7rtv4qZOA/au/Sd9H9q/e2L/FcYsbAIAM0aABAMgQDXpws+MuIDH2r/4mfR/Zv3pj/xbBZ9AAAGSIK2gAADJEg+6D7YbtL9r+SIfXXm573vY15eOV46hxULZvsX1dWftch9dt++22v2r7WtsnjqPOQfWxf6fbvr/l/L1pHHUOyvahti+1fZPtG22f0vZ63c/fYvtX9/N3bEvt19h+wPbr2tap7Tnsc//qfg5/3fYNtq+3fYntR7a9/gjb7yvP31W21/a77alhFzuhXivpRkkHd3n9fRHx6hHWM2zPj4huf693hqSnlI9nS7qw/FonvfZPkv4lIs4cWTXDdb6kj0fE2bZXSlrV9nrdz99i+yfV+PxFxFcknSAVFwKSvi7pQ22r1fYc9rl/Uk3Poe3DJb1G0tMj4ru23y/pHEnvblntFZLujYhjbJ8j6a2SXtLP9rmCXoTtIyT9hKR3jruWMflJSf83Cp+XdKjtJ4y7KEi2D5Z0mqR3SVJE/CAi7mtbrbbnr8/9myTrJf1nRLQP1lTbc9im2/7V3ZSkA2xPqfgF8o62139S0kXl95dKWm/b/WyYBr248yT9jqS9Pdb5mfLW06W2jxxRXcMSkj5he4ftTR1eP1zSbS3Pby+X1cVi+ydJp9j+ku2P2T5ulMUt0dGS5iX9bfkRzDttH9i2Tp3PXz/7J9X3/LU7R9IlHZbX+Ry26rZ/Uk3PYUR8XdKfSLpV0jck3R8Rn2hb7eHzFxG7Jd0v6bH9bJ8G3YPtMyXdGRE7eqz2j5LWRsTxkj6lfb8p1cWpEXGiittov2r7tLbXO/2mV6fo/2L7d7WKofaeKenPJf39qAtcgilJJ0q6MCKeJek7kl7ftk6dz18/+1fn8/ew8vb9WZI+0OnlDsvqcg4lLbp/tT2Hth+t4gr5SZKeKOlA2y9rX63Dj/Z1/mjQvZ0q6Szbt0h6r6QX2N7WukJE3B0R3y+f/rWkk0Zb4tJExB3l1ztVfDZ0ctsqt0tqvStwhPa/hZOtxfYvIh6IiAfL7z8qadr2YSMvdDC3S7o9Iq4qn1+qoqG1r1PX87fo/tX8/LU6Q9LVEfGtDq/V+Rw2dd2/mp/DDZK+FhHzEfGQpA9K+m9t6zx8/srb4IdIuqefjdOge4iIN0TEERGxVsXtmU9HxILfjto+CzpLRZisFmwfaPug5veS/ruk69tW+7CkXyiTpM9RcQvnGyMudSD97J/txzc/D7J9sop/E3ePutZBRMQ3Jd1m+9hy0XpJX25brbbnr5/9q/P5a/NSdb/9W9tz2KLr/tX8HN4q6Tm2V5X7sF7794APS/rF8vuzVfSRvq6gSXEPwPbvS5qLiA9Leo3tsyTtVvFb0cvHWVtFPyTpQ+W/jSlJF0fEx23/iiRFxF9K+qikH5f0VUm7JJ07ploH0c/+nS1ps+3dkr4r6Zx+//Fk4tckbS9vId4s6dwJOn/S4vtX9/Mn26sk/aikV7Usm5hz2Mf+1fYcRsRVti9VcZt+t6QvSppt6xHvkvQe219V0SPO6Xf7jCQGAECGuMUNAECGaNAAAGSIBg0AQIZo0AAAZIgGDQBAhmjQQAZsby1nxLm2nNFnqJMhuJgxqNNsbB2XD/m939jy/Vrb7X9rD6ADGjQwZi6mUDxT0onlkLEbtHDs5bp74+KrAGhHgwbG7wmS7moOGRsRdzWHKLV9ku1/Lif7+KfmyHW2L7d9nu0rXcxDe3K5/ORy2RfLr8d2fdceFnnft9r+gu1/t/28cvkq2+8v7wC8z8W8t+ts/7GKmX6usb293HzD9l+Xdww+YfuAJR09YELRoIHx+4SkI8uGd4HtH5Ek29MqJg84OyJOkvQ3kmZafu7AiPhvkraUr0nSTZJOKyeXeJOkP6paTB/vOxURJ0t6naTfLZdtUTHn7fGS/kDlmPQR8XpJ342IEyJiY7nuUyS9IyKOk3SfpJ+pWiOwHDDUJzBmEfGg7ZMkPU/S8yW9z/brJc1JeoakT5bDlTZUTGnXdEn585+1fbDtQyUdJOki209RMWPO9AAlHbvI+36w/LpD0try++dKOr+s53rb1/bY/tci4poO2wDQggYNZCAi9ki6XNLltq9TMbj+Dkk3RMQp3X6sw/M/kPSZiHix7bXlNqvyIu/bnL1tj/b9P6SvCejbfr65DW5xAx1wixsYM9vHlle8TSdI2inpK5JWlyEy2Z72wsnsX1Iuf66KGY7uVzGV3dfL118+YEmLvW8nn5P0c+X6T5f0X1tee6i8bQ6gAq6ggfF7lKQ/L29R71Yxa9GmiPiB7bMlvd32ISr+vZ4n6Yby5+61faWkgyX9Urnsf6u4xf0bkj7d5/uvt317y/OfVTHDULf37eSC8n2vVTGjz7WS7i9fm5V0re2rJW3tsyZg2WM2K6CGbF8u6bciYm7ctUiS7Yak6Yj4nu0nS7pM0lMj4gdjLg2oLa6gAQzDKkmfKW9lW9JmmjOwNFxBAwCQIUJiAABkiAYNAECGaNAAAGSIBg0AQIZo0AAAZIgGDQBAhv4/3959nOL6eqUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import numpy as np  \n",
    "import math  \n",
    "\n",
    "plt.xlabel('Sepal Length')  \n",
    "plt.ylabel('Petal Length')  \n",
    "plt.title('Sepal vs Petal Length')  \n",
    "plt.scatter(data[\"SepalLength\"], data[\"PetalLength\"], c = \"b\")  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2.5. Bar Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd  \n",
    "data = pd.read_csv(r\"E:\\Data Visualization with Python\\Datasets\\titanic_data.csv\")  \n",
    "data.head()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BarContainer object of 891 artists>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import numpy as np  \n",
    "import math  \n",
    "  \n",
    "plt.xlabel('Gender')  \n",
    "plt.ylabel('Ages')  \n",
    "plt.title('Gender vs Age')  \n",
    "plt.bar(data[\"Sex\"], data[\"Age\"])  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2.6. Histograms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\usman\\Anaconda3\\lib\\site-packages\\numpy\\lib\\histograms.py:824: RuntimeWarning: invalid value encountered in greater_equal\n",
      "  keep = (tmp_a >= first_edge)\n",
      "C:\\Users\\usman\\Anaconda3\\lib\\site-packages\\numpy\\lib\\histograms.py:825: RuntimeWarning: invalid value encountered in less_equal\n",
      "  keep &= (tmp_a <= last_edge)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(array([ 54.,  46., 177., 169., 118.,  70.,  45.,  24.,   9.,   2.]),\n",
       " array([ 0.42 ,  8.378, 16.336, 24.294, 32.252, 40.21 , 48.168, 56.126,\n",
       "        64.084, 72.042, 80.   ]),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import numpy as np  \n",
    "import math  \n",
    "  \n",
    "plt.title('Age Histogram')  \n",
    "plt.hist(data[\"Age\"])  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2.7. Pie Charts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "labels = 'IT', 'Marketing', 'Data Science', 'Finance'  \n",
    "values = [500, 156, 300, 510]  \n",
    "explode = (0.05, 0.05, 0.05, 0.05)   \n",
    "\n",
    "plt.pie(values, explode=explode, labels=labels, autopct='%1.1f%%', shadow=True)  \n",
    "plt.show()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.2. Data Visualization via Seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   total_bill   tip     sex smoker  day    time  size\n",
       "0       16.99  1.01  Female     No  Sun  Dinner     2\n",
       "1       10.34  1.66    Male     No  Sun  Dinner     3\n",
       "2       21.01  3.50    Male     No  Sun  Dinner     3\n",
       "3       23.68  3.31    Male     No  Sun  Dinner     2\n",
       "4       24.59  3.61  Female     No  Sun  Dinner     4"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import seaborn as sns  \n",
    "  \n",
    "plt.rcParams[\"figure.figsize\"] = [10,8]  \n",
    "  \n",
    "tips_data = sns.load_dataset('tips')  \n",
    "  \n",
    "tips_data.head()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3.1. The Dist Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15a74b8d948>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams[\"figure.figsize\"] = [10,8]  \n",
    "sns.distplot(tips_data['total_bill'])  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3.2. The Joint Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x15a74dbb408>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x='total_bill', y='tip', data=tips_data)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x15a74d28708>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.jointplot(x='size', y='total_bill', data=tips_data, kind = 'reg')  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3.3. The Pair Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x15a75031cc8>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 540x540 with 12 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(data=tips_data)  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3.4. The Bar Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>survived</th>\n",
       "      <th>pclass</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>sibsp</th>\n",
       "      <th>parch</th>\n",
       "      <th>fare</th>\n",
       "      <th>embarked</th>\n",
       "      <th>class</th>\n",
       "      <th>who</th>\n",
       "      <th>adult_male</th>\n",
       "      <th>deck</th>\n",
       "      <th>embark_town</th>\n",
       "      <th>alive</th>\n",
       "      <th>alone</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>man</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>no</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C</td>\n",
       "      <td>First</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>C</td>\n",
       "      <td>Cherbourg</td>\n",
       "      <td>yes</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>yes</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>S</td>\n",
       "      <td>First</td>\n",
       "      <td>woman</td>\n",
       "      <td>False</td>\n",
       "      <td>C</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>yes</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>S</td>\n",
       "      <td>Third</td>\n",
       "      <td>man</td>\n",
       "      <td>True</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Southampton</td>\n",
       "      <td>no</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   survived  pclass     sex   age  sibsp  parch     fare embarked  class  \\\n",
       "0         0       3    male  22.0      1      0   7.2500        S  Third   \n",
       "1         1       1  female  38.0      1      0  71.2833        C  First   \n",
       "2         1       3  female  26.0      0      0   7.9250        S  Third   \n",
       "3         1       1  female  35.0      1      0  53.1000        S  First   \n",
       "4         0       3    male  35.0      0      0   8.0500        S  Third   \n",
       "\n",
       "     who  adult_male deck  embark_town alive  alone  \n",
       "0    man        True  NaN  Southampton    no  False  \n",
       "1  woman       False    C    Cherbourg   yes  False  \n",
       "2  woman       False  NaN  Southampton   yes   True  \n",
       "3  woman       False    C  Southampton   yes  False  \n",
       "4    man        True  NaN  Southampton    no   True  "
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "import seaborn as sns  \n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = [8,6]  \n",
    "sns.set_style(\"darkgrid\")  \n",
    "\n",
    "titanic_data = sns.load_dataset('titanic')  \n",
    "\n",
    "titanic_data.head()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15a755b4388>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x='pclass', y='age', data=titanic_data)  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3.5. The Count Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15a7572bd08>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x='pclass', data=titanic_data)  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3.6 The Box Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15a7578a708>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=titanic_data[\"fare\"])  \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.3.7. The Violin Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15a757ebd48>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "sns.violinplot(x='alone', y='age', data=titanic_data)  \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5.4. Data Visualization with Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.4.1. Loading Datasets with Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd  \n",
    "titanic_data = pd.read_csv(r\"E:\\Hands on Python for Data Science and Machine Learning\\Datasets\\titanic_data.csv\")  \n",
    "titanic_data.head()  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.4.2 Plotting Histograms with Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15a758a8888>"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt  \n",
    "titanic_data['Age'].hist()   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.4.3. Pandas Line Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>passengers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>1949</td>\n",
       "      <td>January</td>\n",
       "      <td>112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1949</td>\n",
       "      <td>February</td>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>1949</td>\n",
       "      <td>March</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>1949</td>\n",
       "      <td>April</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>1949</td>\n",
       "      <td>May</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year     month  passengers\n",
       "0  1949   January         112\n",
       "1  1949  February         118\n",
       "2  1949     March         132\n",
       "3  1949     April         129\n",
       "4  1949       May         121"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flights_data = sns.load_dataset('flights')  \n",
    "\n",
    "flights_data.head()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15a7591f6c8>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "flights_data.plot.line( y='passengers', figsize=(8,6))   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.4.4. Pandas Scatter Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15a759a87c8>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "flights_data.plot.scatter(x='year', y='passengers', figsize=(8,6))   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.4.5. Pandas Bar Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sex\n",
      "female    27.915709\n",
      "male      30.726645\n",
      "Name: Age, dtype: float64\n",
      "<class 'list'>\n"
     ]
    }
   ],
   "source": [
    "titanic_data = pd.read_csv(r\"E:\\Data Visualization with Python\\Datasets\\titanic_data.csv\")  \n",
    "titanic_data.head()  \n",
    "sex_mean = titanic_data.groupby(\"Sex\")[\"Age\"].mean()  \n",
    " \n",
    "print(sex_mean)  \n",
    "print(type(sex_mean.tolist()))   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame({'Gender':['Female', 'Male'], 'Age':sex_mean.tolist()})  \n",
    "ax = df.plot.bar(x='Gender', y='Age', figsize=(8,6))   \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.4.6. Pandas Box Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15a75a1d088>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlQAAAHRCAYAAACsDSffAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nO3df1RVdb7/8dcBREVAItAiyyQ1sa51HQIrA6cfkjZaaSZWjIZTK5c54aipmKg0RqWht2uWrmo0NCdNa5yZzO+VUq46/sip6Uako5mmaIpK/FB+yPl8/5glxagofI7uc/D5WGvWig3s8z6fYXOe7n3OwWWMMQIAAECj+Tk9AAAAgK8jqAAAACwRVAAAAJYIKgAAAEsEFQAAgCWCCgAAwFKAkzfudrtVU+O979rg7+/y6vm8GWtnh/Wzw/rZYf0aj7Wz4+3r16yZ/1k/52hQ1dQYFRcfd3KEeoWFBXn1fN6MtbPD+tlh/eywfo3H2tnx9vWLjAw56+e45AcAAGCJoAIAALBEUAEAAFgiqAAAACwRVAAAAJYIKgAAAEsEFQAAgCWCCgAAwBJBBQAAYImgAgAAsERQAQAAWCKoAAAALBFUAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgiaACAACwFOD0AE5ISIjXN98UeGx/XbrEKC9vs8f2BwAAfMslGVTnGz+3vJKnrWMSLvA0AADA13HJDwAAwBJBBQAAYImgAgAAsERQAQAAWCKoAAAALBFUAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgiaACAACwRFABAABYIqgAAAAsEVQAAACWCCoAAABLBBUAAIAlggoAAMASQQUAAGCJoAIAALBEUAEAAFgiqAAAACwRVAAAAJYIKgAAAEsEFQAAgCWCCgAAwBJBBQAAYImgAgAAsERQAQAAWCKoAAAALBFUAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgiaACAACwFHCuL6iurtaECRO0f/9++fn56fnnn1dAQIAmTJggl8ulTp06acqUKfLz89OcOXO0du1aBQQEKD09Xd26dbsY9wEAAMBR5wyqdevW6eTJk/rjH/+oDRs2aPbs2aqurlZaWpri4+OVkZGh3NxcRUVFacuWLVq2bJkOHDigUaNGafny5RfjPgAAADjqnJf8OnTooJqaGrndbpWVlSkgIED5+fmKi4uTJCUkJGjjxo3atm2bevbsKZfLpaioKNXU1Ojo0aMX/A4AAAA47ZxnqIKCgrR//3716dNHx44d0xtvvKGtW7fK5XJJklq1aqXS0lKVlZUpLCys9vtObQ8PDz/rvv39XQoLC/LA3bhwvH0+b+Xv78faWWD97LB+dli/xmPt7Pjy+p0zqBYsWKCePXtqzJgxOnDggIYOHarq6uraz5eXlys0NFTBwcEqLy+vsz0kJKTefdfUGBUXH7cY/8Lz9vm8VVhYEGtngfWzw/rZYf0aj7Wz4+3rFxl59q455yW/0NDQ2jBq3bq1Tp48qa5du2rz5s2SpLy8PMXGxqp79+5av3693G63CgsL5Xa76z07BQAA0FSc8wzVsGHDlJ6erkceeUTV1dUaPXq0brzxRk2ePFnZ2dmKjo5WUlKS/P39FRsbq8GDB8vtdisjI+NizA8AAOA4lzHGOHXj1dU1Xn1q75ZX8rR1TILTY/gkbz9t6+1YPzusnx3Wr/FYOzvevn5Wl/wAAABQP4IKAADAEkEFAABgiaACAACwRFABAABYIqgAAAAsEVQAAACWCCoAAABLBBUAAIAlggoAAMASQQUAAGCJoAIAALBEUAEAAFgiqAAAACwRVAAAAJYIKgAAAEsEFQAAgCWCCgAAwBJBBQAAYImgAgAAsERQAQAAWCKoAAAALBFUAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgiaACAACwRFABAABYIqgAAAAsEVQAAACWCCoAAABLBBUAAIAlggoAAMASQQUAAGCJoAIAALBEUAEAAFgiqAAAACwRVAAAAJYIKgAAAEsEFQAAgCWCCgAAwBJBBQAAYImgAgAAsERQAQAAWCKoAAAALBFUAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgiaACAACwRFABAABYCnB6AE+667WNKqk46dF93vJKnsf2FdoiQLkjb/PY/gAAgHdoUkFVUnFSW8ckeGx/YWFBKi4+7rH9eTLOAACA9+CSHwAAgCWCCgAAwBJBBQAAYImgAgAAsERQAQAAWCKoAAAALBFUAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgiaACAACwRFABAABYIqgAAAAsEVQAAACWCCoAAABLBBUAAIAlggoAAMASQQUAAGCJoAIAALBEUAEAAFgiqAAAACwRVAAAAJYIKgAAAEsEFQAAgCWCCgAAwFLA+XzRvHnz9Mknn6i6ulpDhgxRXFycJkyYIJfLpU6dOmnKlCny8/PTnDlztHbtWgUEBCg9PV3dunW70PMDAAA47pxnqDZv3qzPP/9cS5YsUU5Ojg4ePKisrCylpaXp3XfflTFGubm5ys/P15YtW7Rs2TJlZ2dr2rRpF2N+AAAAx50zqNavX6/OnTtr5MiReuqpp9SrVy/l5+crLi5OkpSQkKCNGzdq27Zt6tmzp1wul6KiolRTU6OjR49e8DsAAADgtHNe8jt27JgKCwv1xhtvaN++fRoxYoSMMXK5XJKkVq1aqbS0VGVlZQoLC6v9vlPbw8PDz7pvf3+XwsKCPHA3fuLJ/fn7+3n1fN7sQqzdpYT1s8P62WH9Go+1s+PL63fOoAoLC1N0dLQCAwMVHR2t5s2b6+DBg7WfLy8vV2hoqIKDg1VeXl5ne0hISL37rqkxKi4+bjH+6Ty5v7CwIK+ez5tdiLW7lLB+dlg/O6xf47F2drx9/SIjz94157zk94tf/EL/+7//K2OMfvjhB504cUK33nqrNm/eLEnKy8tTbGysunfvrvXr18vtdquwsFBut7ves1MAAABNxTnPUP3yl7/U1q1b9dBDD8kYo4yMDLVr106TJ09Wdna2oqOjlZSUJH9/f8XGxmrw4MFyu93KyMi4GPMDAAA47rzeNuHZZ589bduiRYtO2zZq1CiNGjXKfioAAAAfwht7AgAAWCKoAAAALBFUAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgiaACAACwRFABAABYIqgAAAAsEVQAAACWCCoAAABLBBUAAIAlggoAAMASQQUAAGCJoAIAALBEUAEAAFgiqAAAACwRVAAAAJYIKgAAAEsEFQAAgCWCCgAAwBJBBQAAYImgAgAAsERQAQAAWCKoAAAALBFUAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgiaACAACOevjhB9S2bWsFBgaobdvWevjhB5weqcEIKgAA4JiHH35Aa9d+oqFDU3X48BENHZqqtWs/8bmoCnB6AAAAcOlat+5TDRs2XC+/PEutWwfp5ZdnSZIWLnzb4ckahjNUAADAMcYYTZo0tc62SZOmyhjjzECNRFABAADHuFwuTZ8+tc626dOnyuVyOTNQI3HJDwAAOCYx8ZdasOAtSdKMGS/r2Wef1YIFb6lXrzsdnqxhOEMFAAAcs3Tph+rV604tXPi2IiMv18KFb6tXrzu1dOmHTo/WIJyhAgAAjjoVT2FhQSouPu7wNI3DGSoAAABLBBUAAIAlggoAAMASQQUAAGCJoAIAALBEUAEAAFgiqAAAACwRVAAAAJYIKgAAAEsEFQAAgCWCCgAAwBJBBQAAYImgAgAAsERQAQAAWCKoAAAALBFUAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgiaACAACwRFABAABYIqgAAAAsEVQAAACWApwewJOCOszSnR9NcHqMswrq0FZSgtNjAAAAD2tSQXV892htHeO5YAkLC1Jx8XGP7e+WV/I8ti8AAOA9uOQHAABgiaACAACwRFABAABYIqgAAAAsEVQAAACWCCoAAABLBBUAAIAlggoAAMASQQUAAGCJoAIAALBEUAEAAFgiqAAAACwRVAAAAJYIKgAAAEsEFQAAgKXzCqojR44oMTFRu3bt0p49ezRkyBA98sgjmjJlitxutyRpzpw5euihh5ScnKwvv/zygg4NAADgTc4ZVNXV1crIyFCLFi0kSVlZWUpLS9O7774rY4xyc3OVn5+vLVu2aNmyZcrOzta0adMu+OAAAADe4pxB9dJLLyk5OVlt2rSRJOXn5ysuLk6SlJCQoI0bN2rbtm3q2bOnXC6XoqKiVFNTo6NHj17YyQEAALxEvUG1YsUKhYeH64477qjdZoyRy+WSJLVq1UqlpaUqKytTcHBw7dec2g4AAHApCKjvk8uXL5fL5dLf/vY3FRQUaPz48XXOPJWXlys0NFTBwcEqLy+vsz0kJOScN+7v71JYWJDF+Kfz5P78/f28ej5vdiHW7lLC+tlh/eywfo3H2tnx5fWrN6gWL15c+98pKSmaOnWqZsyYoc2bNys+Pl55eXnq0aOHrrnmGs2YMUPDhw/XwYMH5Xa7FR4efs4br6kxKi4+bn8vfsaT+wsLC/Lq+bzZhVi7SwnrZ4f1s8P6NR5rZ8fb1y8y8uwni+oNqjMZP368Jk+erOzsbEVHRyspKUn+/v6KjY3V4MGD5Xa7lZGRYTUwAACALznvoMrJyan970WLFp32+VGjRmnUqFGemQoAAMCH8MaeAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgiaACAACwRFABAABYIqgAAAAsEVQAAACWCCoAAABLBBUAAIAlggoAAMASQQUAAGCJoAIAALBEUAEAAFgiqAAAACwRVAAAAJYIKgAAAEsEFQAAgCWCCgAAwBJBBQAAYImgAgAAsERQAQAAWCKoAAAALBFUAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgiaACAACwRFABAABYIqgAAAAsEVQAAACWCCoAAABLBBUAAIAlggoAAMASQQUAAGCJoAIAALBEUAEAAFgiqAAAACwRVAAAAJYIKgAAAEsEFQAAgCWCCgAAwBJBBQAAYImgAgAAsERQAQAAWCKoAAAALBFUAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgiaACAACOSkzsoTZtQhUYGKA2bUKVmNjD6ZEajKACAACOSUzsoYKCr+VyuSRJLpdLBQVf+1xUEVQAAMAxp2Jq6tTpKi4u0dSp02ujypcQVAAAwFFjx07UiBFPKygoSCNGPK2xYyc6PVKDEVQAAMBRf//7Z/V+7AsIKgAA4BiXy6Xc3P+nlJTBKioqUkrKYOXm/r/a51T5CoIKAAA4JjX1CUnS6tWrFBV1hVavXlVnu68gqAAAgGOysmYqJqZrnW0xMV2VlTXToYkah6ACAACOmThxrHbs2KFp015QcXGJpk17QTt27NDEiWOdHq1BCCoAAOCYnJyFysjIrPMqv4yMTOXkLHR6tAYhqAAAgGOqqio1dGhqnW1Dh6aqqqrSoYkah6ACAACOCQxsroUL366zbeHCtxUY2NyhiRonwOkBAADApSslZagyMzMkSc8887Ref32OMjMzNGxY6jm+07sQVAAAwDGnXs03ffo0TZmSrsDA5ho2LNXnXuVHUAEAAEdlZc1UVtZMhYUFqbj4uNPjNArPoQIAALBEUAEAAEclJvZQmzahCgwMUJs2oUpM7OH0SA1GUAEAAMckJvZQQcHXSkrqo8LCg0pK6qOCgq99LqoIKgAA4JhTMZWT854iIiKUk/NebVT5EoIKAAA46p57kpSQEK8WLQKVkBCve+5JcnqkBuNVfgAAwFHPPTdB7777vpKS7tLq1bl65JGHnB6pwZpcUN3ySp7TI5xVaIsmt9wAAFgJDAxURUWF5s17TT16xGrevNdUUVGhwMBAp0drkCb1CL91TIJH93fLK3ke3ycAAPjJyZMnFRMTo9WrVykq6gpJUkxMjLZv3+7wZA3Dc6gAAIBjOne+XuXldd/Ms7z8uDp3vt6hiRqHoAIAAI4pKSnR3r17FBsbpz17vldsbJz27t2jkpISp0drEIIKAAA4prBwv7p1u0llZaXq0KG9yspK1a3bTSos3O/0aA3SpJ5DBQAAfM8f//iBIiIiav+WX1FRkbp2jXZ6rAbhDBUAAHDU6NEj6/3YF9R7hqq6ulrp6enav3+/qqqqNGLECHXs2FETJkyQy+VSp06dNGXKFPn5+WnOnDlau3atAgIClJ6erm7dul2s+wAAAHxUTExXrV69Sikpg/WHP/xBjz/+uFavXqWYmK5Oj9Yg9QbVypUrFRYWphkzZujYsWN68MEH1aVLF6WlpSk+Pl4ZGRnKzc1VVFSUtmzZomXLlunAgQMaNWqUli9ffrHuAwAA8FHr1m1SYmKPf3vbhK5at26Tw5M1TL1Bde+99yop6ae3f/f391d+fr7i4uIkSQkJCdqwYYM6dOignj17yuVyKSoqSjU1NTp69KjCw8Mv7PQAAMDnnYqnU8+h8kX1BlWrVq0kSWVlZfrtb3+rtLQ0vfTSS3K5XLWfLy0tVVlZmcLCwup8X2lp6TmDyt/fpbCwINv7cEF5+3zeyt/fj7WzwPrZYf3ssH6Nx9rZ8eX1O+er/A4cOKCRI0fqkUceUb9+/TRjxozaz5WXlys0NFTBwcEqLy+vsz0kJOScN15TY7y+RL19Pm/ly//K8Aasnx3Wzw7r13isnR1vX7/IyLO3Tb2v8isqKlJqaqrGjRunhx761x8q7Nq1qzZv3ixJysvLU2xsrLp3767169fL7XarsLBQbreby30AAOCSUe8ZqjfeeEMlJSWaO3eu5s6dK0maNGmSfv/73ys7O1vR0dFKSkqSv7+/YmNjNXjwYLndbmVkZFyU4QEAALyByxhjnLrx6uoarz61xx9HbjxvP23r7Vg/O6yfHdav8Vg7O96+fo2+5AcAAIBzI6gAAAAsEVQAAACWCCoAAABLBBUAAIAlggoAAMASQQUAAGCJoAIAALBEUAEAAEdNnDhW7dpFKjAwQO3aRWrixLFOj9RgBBUAAHDMxIljtWDB25o0aYqKi0s0adIULVjwts9FFUEFAAAck5OzUBkZmRox4mkFBQVpxIinlZGRqZychU6P1iAEFQAAcExVVaWGDk2ts23o0FRVVVU6NFHjEFQAAMAxgYHNtXDh23W2LVz4tgIDmzs0UeMEOD0AAAC4dKWkDNXUqZM0ZUp67TaXy6XU1CccnKrhOEMFAAAcs2vXThlj6mwzxmjXrp0OTdQ4BBUAAHDM2rWfSJKSkvqosPCgkpL61NnuK7jkBwAAHHXVVe306aefKCrqCgUGNtdVV7XT/v37nB6rQThDBQAAHLV//74670PlazElEVQAAMAL7N69S9XV1dq9e5fTozQKl/wAAIDjFix4SwsWvOX0GI3GGSoAAOCYwMDmatOmbZ1tbdq09bn3oSKoAACAY1JShurQoR/qbDt06AelpAx1aKLGIagAAIBjVq36a4O2eyuCCgAAOKawcL8kadq0F1RcXKJp016os91XEFQAAMBRY8ZM0IgRTysoKEgjRjytMWMmOD1SgxFUAADAUZ9++j/1fuwLCCoAAOCov/99m/r2vVsHDhxQ37536+9/3+b0SA1GUAEAAMcMH/6kJOmzz7aoffur9dlnW+ps9xUEFQAAcExW1kyFhV1WZ1tY2GXKyprp0ESNQ1ABAADHJCb2UHHxMSUl9VFh4UElJfVRcfExJSb2cHq0BiGoAACAYwoKvlZSUh/l5LyniIgI5eS8p6SkPioo+Nrp0RqEoAIAAI4qKSlR27atFRgYoLZtW6ukpMTpkRqMP44MAAAc9be/baj9b2NMnY99BWeoAAAALBFUAAAAlggqAADguH//W36+hqACAACO2717l6qrq7V79y6nR2kUnpQOAAAct2DBW1qw4C2nx2g0zlABAADH+PmdOUXOtt1b+da0AACgSXn88d/I5XLJz89fkuTn5y+Xy6XHH/+Nw5M1DEEFAAAck5U1U126xMjtrpEkud016tIlhr/lBwAAcL4mThx72p+ZKSj4WhMnjnVoosYhqAAAgGPeemu+JCkiIlJffvmVIiIi62z3FbzKDwAAOMrfP0BHjhSpW7cb5XK55O8foJqak06P1SAEFQAAcNTP48kY43MxJXHJDwAAwBpBBaDJWLFimRIS4tWiRaASEuK1YsUyp0cCcIngkh+AJmHFimV64YXnNXv2HCUl3aXVq3OVlva0JGnAgEEOTwegqeMMFYAmYfbsmRo4cJDS08cpJKSV0tPHaeDAQZo927feywaAb+IMFYAmYfv2b3T8+HHNnv3az85QjdT33+91ejQAlwCCCkCT0KxZoIqLj2nAgF/VbgsNDVWzZoEOTgXgUsElPwBNQlVVpUpKStS5cxft3PmtOnfuopKSElVVVTo9GoBLAGeoADQZ/v7+2rHjG3XsGF37cU1NjcNTAbgUcIYKQJNRU1Oj2Ng47dnzvWJj44gpABcNQQWgyWjZsqXKykrVoUN7lZWVqmXLlk6PBOASwSU/AE3GiRMnFBwcot2792jgwIE6ceKE0yMBkJSQEK9vvilo8Pe1aRN6xu1dusQoL2+z7VgeRVAB8Bnn80v5s8+2qH37q+ts86VfykBTVN9xNnHiWL311vzTtg8f/qSysnznfeQIKgA+o75fyomJPVRQ8LWSkvroq46P6sadi7V69SrFxHTVunWbLuKUABriVDTl5CxUVVWlAgObKyVlqE/FlCS5jDHGqRuvrq5RcfFxp27+nG55JU9bxyQ4PYZPCgsL8ur/b70d69c4p6LqFGKqcfj5azzWzo63P+5GRoac9XOcoQLQZJyKJ2//pQyg6eFVfgAAAJYIKgAAAEsEFQAAgCWCCgAAwBJBBQAAYImgAgAAsERQAQAAWOJ9qAA47q7XNqqk4qRH93nLK3ke21doiwDljrzNY/sD0PQQVAAcV1Jx0qNvxOnpd6v2ZJwBaJq45AcAAGCJM1QAAKBRuFz/E4IKAAA0Cpfrf0JQAXBcUIdZuvOjCU6PcVZBHdpK4o8tAzg7ggqA447vHs2/cgH4NJ6UDgAAYIkzVAC8gjefBQptwa9KAPXjtwQAx3nycp/0rzjz9D4BoD4EFQBAknTttVfq+PHy2o+Dglrpu+8OODgR4DsIKgBAbUy1a3e1/ud/1uiee+7Wvn3f69prrySqzsOKFcs0e/ZM7dixXZ07X6+0tLEaMGCQ02NdcLxC9ycEFQCg9szUvn3fKybm+tO24+xWrFimp54aXvvxN98U1H7c1KOKV+j+hFf5AQBg4ecxdT7b0TR59AyV2+3W1KlTtX37dgUGBur3v/+92rdv78mbAABcYB9+uFIPPNDf6THgI3iF7r949JbWrFmjqqoqvffee/riiy/04osv6vXXX/fkTQAALqB27a7W9ddfr3btrta+fd87PQ68HK/Q/YlHg2rbtm264447JEk333yzvvrqK0/uHvBaiSselH+LH5we46xqKtpq3YAPnB4DDktIiNc33xTU+zX//hwqSWrTJvSMX9ulS4zy8jZ7bD5ft2LFX5SUdJdWr87VgAG/cnocXGQuY4zx1M4mTZqk3r17KzExUZLUq1cvrVmzRgEBZ+42t9utmhqP3fx5u/nmm/T11/ke21/Xrjfoiy/+4bH9OeGmt5O8Pgj+kbra6TGs8bNnh/U7M28+fr392PXmtZO8f/3OV1M5dps18z/r5zwaVFlZWbrpppvUt29fSVJCQoLy8s5+bbW6usajz+b3NE+/2uBSwtrZYf3ssH4Nd7azUJJ06FDJRZzE97B2nuPtx25kZMhZP+fRV/l17969NqC++OILde7c2ZO7BwBcIGd74CcIgPPj0edQ3XPPPdqwYYOSk5NljNELL7zgyd0DAC6gU/Hk7WcJvM2hQyVnPEtFjF5aPBpUfn5+yszM9OQuAQDwesQoeGNPAAAASwQVAACAJYIKAADAEkEFAABgiaACAACwRFABAABYIqgAAAAsEVQAAACWCCoAAABLBBUAAIAlggoAAMASQQUAAGCJoAIAALBEUAEAAFgiqAAAACy5jDHG6SEAAAB8GWeoAAAALBFUAAAAlggqAAAASwQVAACAJYIKAADAEkEFAABgKcDpARpi8+bNSktLU8eOHSVJlZWV6tevn1JSUhye7Pzcfvvt2rBhQ51teXl5+uijj/Tiiy86NFVd8+fP18aNG+Xn5yeXy6XRo0frxhtvbNS+pk+frscff1xRUVGN+v7Ro0crOTlZ8fHxjfp+b9CQn9mUlBRNnTpV11133cUe02fNnz9f77zzjnJzc9W8eXOnx/FaZzqu//SnP+nxxx/X8uXLFRERoSFDhtT5ni+//FKzZ8+WMUZut1uJiYlKTU116B44x9OPO5fycb5v3z71799fN9xwQ+22+Ph4Pf300w5O5Tk+FVSS1KNHD82aNUuSVFVVpXvvvVf333+/QkNDHZ7M9+3cuVOffPKJlixZIpfLpYKCAo0fP14rV65s1P4mTZrk4Ql9Ez+zF86f//xn9e3bV3/96181YMAAp8fxSo09rjMzM/XSSy/puuuuU3V1tZKTk9WjRw917dr1Ik3uPTiGPadjx47KyclxeowLwueC6ufKysrk5+enb775RnPmzJEkVVRU6KWXXlJUVJSeeeYZlZWVqaKiQuPGjVN8fLwmTJigvXv3qrKyUsOHD1ffvn21ZcsWzZo1S/7+/rr66quVmZmpP//5z1q3bp0qKiq0d+9ePfHEExowYIC+/PJLTZs2Ta1atdLll1+u5s2b68UXX1ROTo7+8pe/yOVyqW/fvvr1r3+tCRMmqLi4WMXFxZo3b17t3Lt27VJ6erpatmypli1bqnXr1k4tYR3h4eEqLCzU+++/r4SEBMXExOj999+v8y+qJUuWqKioSA8++KBGjBihsLAwJSQkaMWKFfroo4/kcrk0bdo03XbbbXrnnXc0depUjRs3Tq+++qratWunVatWadu2bXrmmWc0adIkHTt2TJL03HPP6frrr9fixYu1bNkyRUZG6siRIw6viOf9/Gd25syZMsaobdu2mjlzZu3XHDx4UFOnTvVXjn0AAAnTSURBVFVlZaWKi4s1cuRI3X333Zo1a5Y2bdokt9ut++67T8OGDdPixYv14Ycfys/PT927d9f48eMdvHcX1+bNm3XNNdcoOTlZ48aNa/Dxeak413EtSWvWrNGqVatUUVGh5557Tt26dVNUVJQWL16sAQMGKCYmRkuWLFFgYKBWrFih3NxclZWV6dixYxo5cqSSkpKcvZMXUX2PO82aNavzezEuLk7Tp08/7Th/7bXXVFRUpBMnTig7O1tXX321k3fJUTU1NcrIyNDBgwd17NgxJSQkKC0t7bTHzzfffFNbt26VMUbDhg1Tnz59nB79dMaHbNq0yfTo0cM89thjJiUlxaSmppq1a9eaRYsWmYMHDxpjjHn99dfN3LlzzY4dO8zAgQNNaWmp+e6778zatWtNaWmp6dWrlzly5Ig5cuSIWblypXG73aZ3796mqKjIGGPMrFmzzHvvvWeWL19uUlNTjTHG7N692yQlJRljjHnggQfMjh07jDHGZGdnm/Hjx5t//vOfJjk52Zw8edLU1NSYlJQUs2vXLjN+/Hjzhz/8oXb+2267zRhjzKhRo8z69euNMcbMmzfPjB8//qKs3/n46quvzIQJE0xiYqJJSkoyH3/8sXnsscfMzp07jTHGvPvuu+bVV18133//vYmPjzeVlZXGGGOeeeYZs2XLFlNZWWn69u1rqqura79v8eLF5r//+7+NMcY88cQTZvv27ebll182ixcvNsb8a32Tk5NNSUmJ6d27t6msrDRVVVXmV7/6ldm0aZMzC+EhZ/uZ7devX+2aLlq0yHz11Ve167Vhw4ba+71t2zYzbNgwY4wxCQkJZu/evaaystIsWbLEGGPMgAEDzOeff26MMWbx4sWmurragXvpjDFjxphPP/3UGGNMcnKy+eKLLxp0fF5K6juuX331VTN58mRjjDE7duwwDzzwgDHGmNLSUjNnzhwzcOBAExcXZzIzM01lZaVZvny5GTZsmKmpqTGHDx82vXr1atI/dw153Pn334tnO84//PBDY4wxr776qpk/f74zd8wB33//vfnP//xP89hjj9X+77PPPjNLly41xhhTUVFh4uLijDGmzuPn2rVrTVpaWu3X9O/f3/z444+O3If6+NwZqp+fej1lzZo1mj59uoKCgvTDDz+oe/fu6tSpkx599FH97ne/08mTJ5WSkqLg4GBNnjxZkydPVllZmfr376+jR4/q0KFDSktLk/Svf2ncfvvtuuaaa9SlSxdJ0pVXXqmqqipJ0qFDh9SpUydJ0i9+8Qt99NFH2rFjhwoLCzVs2DBJ0o8//qi9e/dKkjp06HDaffjnP/+pbt26SZK6d++ub7/91vML1Qh79uxRcHCwsrKyJEn/93//pyeffFIRERG1X2N+9peK2rVrp8DAQEnSww8/rA8++ECHDx/WnXfeqYCAn360+vfvryFDhmjQoEEqKytT586dtWPHDm3atEmrVq2SJJWUlOjbb79Vx44da/d5ao183Zl+ZtPT02ufQ/Hoo4/W+VxkZKRef/11vf/++3K5XDp58qQkKTs7W9nZ2SoqKtIdd9whScrKytLbb7+tmTNn6uabb67z/09T9uOPPyovL09Hjx5VTk6OysrKtGjRogYdn9HR0Q7eg4vnfI7rW265RZLUqVMnHT58WJWVlcrPz9fIkSM1cuRIHTt2TOnp6XrvvffUqlUr3XLLLfLz81NERIRCQ0N19OhRtWnTxpH7dzGc7+OOVPf34pEjR854nJ96XmpERISKioouxl3wGv9+ya+srEx/+tOftGnTJgUHB9c+1ko/PX7u2LFD+fn5tc9bO3nypAoLC73ukqvPBdWZPPfcc1qzZo2Cg4M1fvx4GWO0fft2lZeXa/78+Tp06JCSk5N1ww03KD8/X6+99poqKyuVmJiofv366YorrtDcuXMVEhKi3NxcBQUF6cCBA3K5XKfd1hVXXKGdO3eqY8eO+sc//iFJio6OVseOHfXmm2/K5XJpwYIF6ty5sz7++OMz7iM6Olqff/65EhIS9NVXX13w9Tlf27dv15IlS/TGG2+oefPm6tChg0JCQhQWFqbDhw/ruuuu09dff622bdtKkvz8fnqR6K233qoZM2bohx9+UEZGRp39BgcH68Ybb1RWVlbt81yio6PVv39/9evXT0eOHNGyZct09dVXa+fOnaqoqFCzZs1UUFCg/v37X7wFuIjatGmj7777Ttdee63mz59fJ7z/67/+S4MGDVJiYqKWL1+uDz74QFVVVfr444+VnZ0tY4zuu+8+3XfffVq6dKmmTZum5s2ba/jw4fr8888VFxfn4D27OFauXKmBAwfWXuI8ceKE7rrrLrVo0eK8j89LxdmOa39//9qv+fLLL9WvXz9t375dUVFRcrlcGjdunN5880117txZl112ma666qraUMjPz5ckFRUVqaysTJdffrkj981JZ3rcker+XqzvOMe/rFixQiEhIcrMzNSePXu0dOnS2rU89fgZHR2t+Ph4Pf/883K73Zo7d67atWvn5Nhn1CSC6v7779fDDz+s0NBQRURE6NChQ7r22mv12muv6cMPP1SzZs3029/+VpGRkTp8+LAeeOABBQUFKTU1VYGBgZo0aZKefPJJGWPUqlUrvfzyyzpw4MAZb2vKlClKT09XUFCQmjVrprZt26pLly669dZbNWTIEFVVValbt2610XG2fYwePVpvvfWWwsPDvebVSb1799auXbs0aNAgBQUFyRijZ599Vs2aNVNmZqauvPLKs/4r1OVyKSkpSRs3blT79u1P+/ygQYP0m9/8Ri+88IIk6amnntKkSZO0dOlSlZWV6emnn1Z4eLieeeYZJScnKzw8XC1btryg99dJ06ZNU3p6uvz8/BQZGalhw4bpnXfekSTde++9mj59uubNm6crr7xSx44dU2BgoFq3bq37779frVu31u23366oqChdf/31euihh3TZZZepbdu2uummmxy+ZxfHsmXL9PLLL9d+3LJlS/Xu3VsRERHWx2dTc7bjeuHChbVfs2/fPv36179WVVWVMjMzFRgYqNmzZysjI0M1NTVyuVz6j//4Dw0cOFArV65UUVGRhg4dqtLSUk2ZMqVOnF0qzvS48+/qO87xL7feeqt+97vfadu2bWrZsqXat29/2lreeeed2rJlix555BEdP35cd999t4KDgx2a+Oxc5lK5RuAhixcvVp8+fRQeHq5Zs2apWbNmTeYln4Cv4/i88FasWKFvv/1WY8eOdXoUwKs0iTNUF9Pll1+u1NRUBQUFKSQkxGvePwoAxycA53CGCgAAwBJ/egYAAMASQQUAAGCJoAIAALBEUAEAAFgiqAAAACwRVAAAAJb+P6G3Ejig7K3UAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "titanic_data = pd.read_csv(r\"E:\\Data Visualization with Python\\Datasets\\titanic_data.csv\")  \n",
    "titanic_data.plot.box(figsize=(10,8))   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise 5.1\n",
    "\n",
    "**Question 1:**\n",
    "\n",
    "Which Pandas function is used to plot horizontal bar plot?\n",
    "\n",
    "A- horz_bar()\n",
    "\n",
    "B- barh()\n",
    "\n",
    "C- bar_horizontal()\n",
    "\n",
    "D- horizontal_bar()\n",
    "\n",
    "\n",
    "**Question 2:**\n",
    "\n",
    "To create a legend, the value for which of the following parameter is needed to be specified?\n",
    "\n",
    "A- title\n",
    "\n",
    "B- label\n",
    "\n",
    "C- axis\n",
    "\n",
    "D- All of the above\n",
    "\n",
    "\n",
    "**Question 3:**\n",
    "\n",
    "How to show percentage values on a matplotlib Pie Chart?\n",
    "\n",
    "A - autopct = '%1.1f%%'\n",
    "\n",
    "B - percentage = '%1.1f%%'\n",
    "\n",
    "C - perc = '%1.1f%%'\n",
    "\n",
    "D - None of the Above\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exercise 5.2\n",
    "\n",
    "Plot two scatter plot on the same graph using tips_dataset. In the first scatter plot, display values from total_bill column on x-axis and from the tip column on y-axis. The color of the first scatter plot should be green. In the second scatter plot, display values from the total_bill column on x-axis and from the size column on y-axis. The color of the second scatter plot should be blue and markers should be x."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Solutions:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15a76d23148>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x=\"total_bill\", y=\"tip\", data=tips_data, color = 'g')\n",
    "sns.scatterplot(x=\"total_bill\", y=\"size\", data=tips_data, color = 'b', marker = 'x')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
